Automated photomask inspection apparatus and method

ABSTRACT

A method and apparatus for inspecting patterned transmissive substrates, such as photomasks, for unwanted particles and features occurring on the transmissive, opaque portions and at the transition regions of the opaque and transmissive portions of the substrate. A transmissive substrate is illuminated by a laser through an optical system comprised of a laser scanning system, individual transmitted and reflected light collection optics and detectors collect and generate signals representative of the light transmitted and reflected by the substrate as the substrate is scanned repeatedly in one axis in a serpentine pattern by a laser beam which is focused on the patterned substrate surface. The defect identification of the substrate is performed using only those transmitted and reflected light signals, and other signals derived from them, such as the second derivative of each of them. The actual defect identification is then performed by comparing combinations of at least two of those measured and derived signals. Simultaneously, defect and particle inspection using the same measured transmitted and reflected light signals. Additionally, phase shift and line widths on the substrate can also be performed simultaneously using the same transmitted light signal that is collected for defect analysis.

CROSS REFERENCE

This application is a continuation of patent application Ser. No.08/274,310, filed on Jul. 13, 1994, now U.S. Pat. No. 5,563,702, whichis a Continuation-In Part of patent application Ser. No. 07/202,868entitled "Automated Photomask Inspection Apparatus" filed Feb. 25, 1994,U.S. Pat. No. 5,572,598, which is a continuation application having Ser.No. 07/748,984 filed Aug. 22, 1991, now abandoned, in the names of MarkWihl, Tao-Yi Fu, Marek Zywno, Damon F. Kvamme, and Michael E. Fein andassigned to the same assignee as the present application.

FIELD OF THE INVENTION

The present invention relates generally to electro-optical inspectionsystems, and more particularly to an automated photomask inspectionapparatus for detecting defects on optical masks and reticles and thelike.

BACKGROUND OF THE INVENTION

Integrated circuits are made by photolithographic processes which usephotomasks or reticles and an associated light source to project acircuit image onto a silicon wafer. A high production yield iscontingent on having defectless masks and reticles. Since it isinevitable that defects will occur in the mask, these defects have to befound and repaired prior to using the mask.

Automated mask inspection systems have existed for over 15 years. Theearliest such system, the Bell Telephone Laboratories AMIS system (JohnBruning et al., "An Automated Mask Inspection System--AMIS", IEEETransactions on Electron Devices, Vol. ED-22, No. 7 July 1971, pp 487 to495), used a laser that scanned the mask. Subsequent systems used alinear sensor to inspect an image projected by the mask, such asdescribed by Levy et al. (U.S. Pat. No. 4,247,203, "Automatic PhotomaskInspection System and Apparatus") who teach die-to-die inspection, i.e.,inspection of two adjacent dice by comparing them to each other.Alternately, Danielson et al. (U.S. Pat. No. 4,926,489, "ReticleInspection System") teach die-to-database inspection, i.e. inspection ofthe reticle by comparison to the database from which the reticle wasmade.

As the complexity of integrated circuits has increased, so has thedemand on the inspection process. Both the need for resolving smallerdefects and for inspecting larger areas have resulted in much greaterspeed requirements, in terms of number of picture elements per secondprocessed. The increased demands have given rise to improvementsdescribed in a number of subsequently issued patents, such as U.S. Pat.No. 4,247,203, entitled "Automatic Photomask Inspection System andApparatus", Levy et al., issued Jan. 27, 1981; U.S. Pat. No. 4,579,455,entitled "Photomask Inspection Apparatus and Method with Improved DefectDetection", Levy et al., issued Apr. 1, 1986; U.S. Pat. No. 4,633,504,entitled "Automatic Photomask Inspection System Having Image EnhancementMeans", Mark J. Wihl, issued Dec. 30, 1986; and U.S. Pat. No. 4,805,123,entitled "Automatic Photomask Inspection and Reticle Inspection Methodand Apparatus Including Improved Defect Detector and AlignmentSubsystem", Specht et al., issued Feb. 14, 1989. Also of relevance issome prior art in the wafer inspection area, such as U.S. Pat. No.4,644,172, entitled "Electronic Control of an Automatic Wafer InspectionSystem", Sandland et al., issued Feb. 17, 1987.

Another force driving the development of improved inspection techniquesis the emergence of phase shift mask technology. With this technology itwill be possible to print finer line widths, down to 0.25 micrometers orless. This technology is described by Burn J. Lin, "Phase-Shifting andOther Challenges in Optical Mask Technology", Proceedings of the 10thAnnual Symposium on Microlithography, SPIE,--the International Societyof Optical Engineering, Vol. 1496, pages 54 to 79.

The above improvements teach the automatic detection of defects onconventional optical masks and reticles. In all of these systems,conventional lighting is used and the images are captured by lineararray sensors. These two system choices limit the signal-to-noise ratioand hence the speed of inspection.

Additionally, a photomask is used in the semiconductor manufacturingindustry for the purpose of transferring photolithographic patterns ontoa substrate such as silicon, gallium arsenide, or the like during themanufacture of integrated circuits. The photomask is typically composedof a polished transparent substrate, such as a fused quartz plate, onwhich a thin patterned opaque layer, consisting of figures, has beendeposited on one surface. Typically the patterned opaque layer ischromium with a thickness of 800 to 1200 angstroms. This layer may havea light anti-reflection coating deposited on one or both surfaces of thechromium. In order to produce functioning integrated circuits at a highyield rate, the photomasks need to be free of defects. A defect isdefined here as any unintended modification to the intendedphotolithographic pattern caused during the manufacture of the photomaskor as a result of the use of the photomask. Defects can be due to, andnot limited to, a portion of the opaque layer being absent from an areaof the photolithographic pattern where it is intended to be present, aportion of the opaque layer being present in an area of thephotolithographic pattern where it is not intended to be, chemicalstains or residues from the photomask manufacturing processes whichcause an unintended localized modification of the light transmissionproperty of the photomask, particulate contaminates such as dust, resistflakes, skin flakes, erosion of the photolithographic pattern due toelectrostatic discharge, artifacts in the photomask substrate such aspits, scratches, and striations, and localized light transmission errorsin the substrate or opaque layer. During the manufacture of photomasks,automated inspection of the photomask is performed in order to ensure afreedom from the aforementioned defects.

There are, at present, two methods for the inspection of patterned masksor reticles. One of those inspection methods is die-to-die which usestransmitted light to compare either two adjacent dies or a die to theCAD database of that die. These comparison-type inspection systems arequite expensive because they rely on pixel-by-pixel comparison of allthe dies and, by necessity, rely on highly accurate methods of alignmentbetween the two dies used at any one time for the comparison. Apart fromtheir high costs, this method of inspection is also unable to detectparticles on opaque parts of the reticle which have the tendency tosubsequently migrate to parts that are transparent and then cause adefect on the wafer. This method of inspection is described in U.S. Pat.Nos. 4,247,203 and 4,579,455, both by Levy et al.

The second method of the prior art for inspection of patterned masks isrestricted to locating particulate matter on the mask. It makes use ofthe fact that light scatters when it strikes a particle. Unfortunately,the edges of the pattern also cause scattering and for that reason thesesystems are unreliable for the detection of particles smaller than 1micrometer. Such systems are described in a paper entitled "AutomaticInspection of Contaminates on Reticles" by Masataka Shiba et al., SPIEVol. 470 Optical Microlithography III, pages 233-240 (1984).

Recently Wihl et al., in the U.S. patent application of which thispatent application is a Continuation-In-Part application (Ser. No.07/784,984) describes a method for the inspection of photomasksubstrates utilizing both reflected and transmitted light and suggestedthe use of both to classify defects.

It would be advantageous to extend the use of both reflected andtransmitted light to obviate the need for using a die-to-die comparisonfor the detection of particles. It would also be advantageous to have asystem that can also identify the location of the defect on thesubstrate without using a die-to-die comparison. Various embodiments ofthe present invention provide such a system and method.

SUMMARY OF THE PRESENT INVENTION

An important object of the first aspect of the present invention is toprovide a novel defect detection apparatus which can use bothtransmitted and reflected light to inspect a substrate.

Another object of the first aspect of the present invention is toprovide a device of the type described in which surface elevations abovea reference elevation are optically determined using interferrometricprinciples and used as indicators of defects.

Another object of the first aspect of the present invention is toprovide a device of the type described which uses the same opticalsystem to detect defects and measure line widths.

Briefly, a preferred embodiment of the first aspect of the presentinvention includes an X-Y stage (12) for transporting a substrate (14)under test in a serpentine path in an X-Y plane, an optical system (16)including a laser (30), a transmission light detector (34), a reflectedlight detector (36), optical elements defining reference beam paths andilluminating beam paths between the laser, the substrate and thedetectors and an acousto-optical beam scanner (40, 42) forreciprocatingly scanning the illuminating and reference beams relativeto the substrate surface, and an electronic control, analysis anddisplay system for controlling the operation of the stage and opticalsystem and for interpreting and storing the signals output by thedetectors. The apparatus can operate in a die-to-die comparison mode ora die-to-database mode.

One advantage of the first aspect of the present invention is that ituses a laser light source and hence has a much higher brightness to scanthe mask. It differs from the AMIS system described by Bruning et al. inthat it employs an electro-optical deflection method instead of amechanical system. Obviously the electro-optical method is faster andmore flexible than a mechanical device. However, even conventionalelectro-optical deflections do not have sufficient speed to meet systemrequirements. In the first aspect of the present invention the speed isfurther enhanced by the use of a deflection apparatus previouslydescribed for laser beam recording by U.S. Pat. No. 3,851,951 to JasonH. Eveleth, entitled "High Resolution Laser Beam Recorder withSelf-Focusing Acousto-Optic Scanner", issued Dec. 3, 1974.

Another advantage is the use of a stage that has only two degrees offreedom. Prior art also incorporated a rotational capability at aconsiderable cost and complexity. In the first aspect of the presentinvention the effective direction of scanning is controlled by drivingboth axes of the stage simultaneously.

Another significant departure from previous art is the ability of thepresent system to simultaneously detect defects with both transmittedand reflected light. This capability is significant because theadditional information can be helpful in determining the nature of thedefect and thereby permits the automatic classification of defects.

Yet another advantage of the first aspect of the present invention isits ability to inspect phase shift masks. It is anticipated that phaseshift mask technology will be used in the 1990's to achieve line widthsof 0.10 micrometers. In the first aspect of the present invention thephase shift material can be measured at all points on a mask area at thenormal scanning speed of the system.

Also advantageous is the ability of the present system to performlinewidth measurement on the mask. This is a significant advantagebecause heretofore two different types of instruments were employed todo both defect detection and linewidth measurement. The ability to use asingle instrument results in a saving of time and, possibly moreimportant, in less handling of the mask, which in turn is significant incontamination control.

A novel feature of the first aspect of the present invention is theautofocusing method employed. Previous mask inspection systems usedautofocus systems that were affected by the pattern on the mask. Thefirst aspect of the present invention functions independently of thepattern.

A significant innovation of the present system is also the two-axispreloading of the stage air bearings. Exceptional stiffness is achievedby this angular loading method.

Also new is the method of correcting for variations of light intensity.In the prior art the spatial non-uniformity of the illumination wasdetermined before an inspection but no provisions existed forcompensating for changing non-uniformity during inspection or, morelikely, variations of the absolute level of intensity during theinspection. In the first aspect of the present invention the intensityis constantly monitored and immediately compensated in real time. Hence,variations of the primary light source with time do not affect theaccuracy of the inspection process.

Yet another new capability of the first aspect of the present inventionis to inspect the mask at substantially the same wave length as used forwafer printing (exposure) through the mask. With advances in technology,increasingly shorter wavelengths are used for printing. Because theappearance of defects changes depending on the wavelength of theillumination, it is important to employ approximately the samewavelength light source for both inspection and printing.

In accordance with the second aspect of the present invention there isprovided a novel method and apparatus for the inspection of photomasksat a high sensitivity to detect submicron particulate contamination,chemical stains and residues, and localized transmission variations byutilizing synchronized transmitted and reflected light signals (i.e.from the same location on the substrate with either the same light beamor two light beams of equal intensity and cross sectional size and shapeilluminating the same location on the substrate).

The second aspect of the present invention also provides a novelapparatus for, and method of, inspection of a substrate which obviatesthe requirement for a reference database or a multiplicity of identicalphotolithographic images for the detection of particulate contamination,chemical stains and residues, and localized transmission variations.

Additionally, the second aspect of the present invention provides amethod and an automatic system that does not require an alignmentsubsystem to inspect photomasks for the detection of particulatecontamination, chemical stains and residues, and localized transmissionvariations.

Further, the second aspect of the present invention provides a novelapparatus and method for the detection of particulate contamination,chemical stains and residues, and localized transmission variationslocated in close proximity and in contact with the edges of figures.

Still further, the second aspect of the present invention provides anovel apparatus and method for the automatic classification of defectsdetected according to their type using only transmitted and reflectedlight information.

The second aspect of the present invention is based upon a laserscanner, optical conditioning subsystem, a stage, reflectance andtransmission detectors, and an autofocus subsystem as disclosed in theabove cross-referenced Wihl patent application.

These and other objects and advantages of all of the aspects of thepresent invention will no doubt become apparent to those skilled in theart after having read the following detailed disclosure of the preferredembodiments illustrated in the several figures of the drawing.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a simplified functional block diagram of a laser maskinspection system in accordance with the first aspect of the presentinvention.

FIG. 2 is a more detailed schematic representation of the opticalsubsystem depicted in FIG. 1.

FIG. 3 is a diagram illustrating the scanning path used in thedie-to-die inspection mode.

FIG. 4 is a diagram illustrating the scanning path used indie-to-database inspection mode.

FIGS. 5 and 6 are diagrams illustrating possible beam cross sectionsused in the autofocus system.

FIG. 7 is a partially broken perspective drawing illustrating the X-Ystage.

FIG. 8 is a cross-section taken along the line 8--8 of FIG. 7 showingdetails of the construction frame of the stage.

FIG. 9 is a cross-section taken along the line 9--9 of FIG. 7 showingother details of the construction frame of the stage.

FIG. 10 is an illustration of a cross-section of a typical phase-shiftmask showing in exaggerated scale an illustration of the phase-shiftedoutput of the reflected beam detector.

FIG. 11 is an illustration of the sinusoidally varying detected signalintensity as the mask is scanned in phase shift measurement mode.

FIG. 12 is a block diagram depicting a phase-locked loop subsystem usedto detect phase-shift material thickness.

FIGS. 13a and 13b are simplified schematic diagrams respectivelydepicting operation of the optical subsystem used for measuring thephase-shift material thickness in the transmitted and reflected lightmodes.

FIG. 14 is an illustration used to describe the method of linewidthmeasurement.

FIG. 15 is a simplified functional block diagram of the laser maskinspection system of the second aspect of the present invention and amodification of FIG. 1.

FIG. 16 is a more detailed schematic representation of the opticalsubsystem depicted in FIG. 15 and a modification of FIG. 2.

FIG. 17 is a normalized plot of the transmitted light and reflectedlight signals detected by sensors of the second aspect of the presentinvention for one scan of the laser scanner.

FIG. 18 is a normalized plot of the transmitted, reflected, andsummation signals for a optical subsystem of the second aspect of thepresent invention showing the effect of particulate contamination onthose signals.

FIG. 19 is a graph of the relationship between transmitted and reflectedlight signal pairs in the absence of defects as per the second aspect ofthe present invention.

FIG. 20 is a graph as in FIG. 19 which shows the additional loci ofpoints resulting from particulate contamination on the opaque layer, atthe edge of a feature, and on the photomask substrate as per the secondaspect of the present invention.

FIG. 21 is a graph of transmitted light values versus the secondderivative transmitted light values as per the second aspect of thepresent invention.

FIG. 22 is a graph of reflected light values versus the secondderivative reflected light values as per the second aspect of thepresent invention.

FIG. 23a is a pixelized transmission image of the substrate beinginspected.

FIG. 23b is a pixelized second derivative transmission image, derivedfrom the pixelized transmission image of the substrate being inspected.

FIG. 24 is a block diagram shown in three tiers with the transmissionand reflection observed pixel maps as input signals which are operatedon by a selected number of different filters, the filter output signalsbeing combined pair-wise in the second layer, and the third layerproviding a merge function to identify all of the defects detected fromeach of the pair-wise signal combinations of the second layer.

FIG. 25 is a typical representation of a BPN neural network.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIRST ASPECT OF THE PRESENT INVENTION

Referring now to the drawing, a block diagram of an automatic opticalinspection system in accordance with the first aspect of the presentinvention is shown at 10. The system is capable of inspectingsubstrates, such as reticles, photomasks, semi-conductor wafers andphase shift masks.

The system can perform several types of inspection: transmitted lightinspection, reflected light inspection, simultaneous reflected andtransmitted inspection, and phase shift measurement. In transmittedlight inspection, light impinges on the substrate, a photomask forexample, and the amount of light transmitted through the mask isdetected. In reflected light inspection, the light reflecting from asurface of the substrate under test is measured. During phase shiftinspection, the amount of phase shift between two reflected coherentlight beams is detected at each point on the mask while transmittedlight inspection takes place concurrently. The phase shift isproportional to the relative elevation of the surface from which thebeams are reflected. As will be explained below, the transmitted lightsignal is used to qualify the phase-shift signal. In addition to thesedefect detection operations, the system is also capable of performingline width measurement.

In all of the defect detection operations a comparison is made betweentwo images. In die-to-die inspection mode two areas of the substratehaving identical features (dice) are compared with respect to each otherand any substantial discrepancy is flagged as a defect. In thedie-to-database inspection mode a defect is detected by comparing thedie under test with corresponding graphics information obtained from theCADS (computer aided database system) database from which the die wasderived. In the latter case the CADS database is converted to an imageformat as explained in U.S. Pat. No. 4,926,489. (Danielson at al.,"Reticle Inspection System", issued May 15, 1990).

As depicted in the simplified block diagram of FIG. 1, a preferredembodiment of the system 10 is comprised of a stage 12 for carrying asubstrate 14 to be inspected, an optical subsystem 16, a data baseadaptor 18, an electronics subsystem 20, a display 22, a controlcomputer 24 and a keyboard 26.

The Stage

Although a preferred embodiment of the stage 12 will be described indetail below, it suffices at this point to say that the stage is aprecision device driver under control of subsystem 20 and is capable ofmoving the substrate 12 under test in a serpentine fashion, within asingle plane, relative to the optical axes of the optical subsystem 16so that all or any selected part of the substrate surface may beinspected.

Optical Subsystem

A detailed block diagram of the optical subsystem 16 is shown in FIG. 2and is essentially a laser scanner apparatus including a light source302 and associated optics which cause a beam 32 of coherent light to bedeflected over a small angle, i.e., from one side to the opposite sideof the optical axis defined by the optical subsystem 16. As will befurther described below, the beam sweep is in a direction such that,after passing through the optical system, it is directed parallel to theY-axis as viewed at the substrate 14. As the beam is swept, the stage 12carrying the substrate 14 under test is caused to move back and forth inthe direction of the X-axis, being incremented in the Y-direction at theend of each traverse so that the beam 32 is caused to sweep along aserpentine path 31 across a plurality of identified substrate subareas33, 35, 37 (individual dice in the case of a photomask) as indicated inFIGS. 3 and 4. In this manner the entire surface area of the substrate(mask) 14 is swept in a series of contiguous swaths 39 by the laserbeam. In the case of a transparent or partially transparent substrate,detection of the image is accomplished by a transmission detector 34. Inthe case of a reflective or partially reflective substrate, the lightreflected from the substrate is detected by a reflected light detector36. As will be explained in more detail later, phase shift maskinspection is carried out by using both of these detectorssimultaneously.

The light source 30 of the system is a laser, such as the Model5490A5L-00C-115 made by Ion Laser Technology of Salt Lake City, Utah.The light beam 32, emitted by the laser 30, first passes through aspatial filter 38 and is then deflected by the combination of twoacousto optic elements; an acousto-optic prescanner 40 and anacousto-optic scanner 42. These two elements deflect the light beam inthe Y-direction and focus it in the X-direction in a manner similar tothat described in U.S. Pat. No. 3,851,951. (Jason H. Eveleth, "HighResolution Laser Beam Recorder with Self-focusing Acousto-opticScanner", issued Dec. 3, 1974). The deflection system also includes abeam expander 44 and a quarter wave plate 46.

When the beam emerges from the scanner 42, it is convergent in theY-direction, but collimated in the X-direction. A cylindrical lens 50then also focuses the beam in the X-direction, with the focal plane forboth X and Y axes lying at a field stop 52. The beam next passes througha quarter wave plate 54 and a relay lens 56.

The beam is then reflected by a mirror 58, the sole function of which isto fold the optical path. The redirected beam then enters a cube beamsplitter 60 which divides it into paths 62 and 64. The latter path isused only in the phase measurement mode and is otherwise blocked by ashutter 63.

The beam continuing along path 62 is reflected by an oscillating mirror65 which is held fixed during the inspection operation and is used onlyfor displaying an image to an operator on an image display (not shown inFIG. 2) during alignment and review. A dove prism 66 is used to rotatethe direction of the scan about the optical axis. The output of prism 66is fed to one of the telescopes 68 and 70 mounted on a rotatable turret72. The purpose of these telescopes is to vary the size of the scanningspot on the substrate 14 and thereby allow selection of the minimumdetectable defect size. Since changing the magnification also varies thelength of the scan, the swath width is also changed and therefore theinspection speed. (Only two telescopes are shown but obviously anynumber of telescopes, and therefore spot sizes, can be used.)

From the telescope the beam passes to a mirror 74 and then to a beamsplitter 76 where the path is again split. The reflected portion of beam78 is directed to a detector 80 which serves as a monitor of the beamintensity variation. The unreflected portion of the beam passes throughan objective lens 82 which focuses the beam onto the substrate 14. Lightpassing through the substrate 14 is then collected by a condenser lens84 and a collector lens 86, and focused onto the transmission detector34.

Autofocus Subsystem

The autofocus function is based upon a monitoring of the shape of thelight beam cross-section after it is passed through some anamorphicelements. The basic principle underlying the implementation is that acylindrical lens produces astigmatism. In such a case a focussed beamfirst passes through best focus in one direction and then through bestfocus in the perpendicular direction. In between these two focal pointsalong the beam path the beam cross section is oblong in one directionand transitions along the path through points where the beam crosssection is circular and then oblong in a direction perpendicular to theprevious direction. In this invention the optimum focus of the lightimpinging on the substrate is detected by monitoring the beam crosssection of light reflected from the substrate 14. The shape of the beamcross section is monitored by two silicon quadrature photodiodes 90 and92, such as made by Silicon Detector Corporation of Newbury Park, Calif.

As is explained in more detail below, the actual autofocus systemconsists of two optical paths which differ from each other in thedirection of the astigmation. In one path the cylindrical lens has nocurvature when viewed in the X-direction while in the other path, thecylindrical lens has no curvature in the Y-direction.

The autofocus beam 93 is split off from the reflected beam 95 directedalong reflected detector path by a beam splitter 94, and is redirectedtoward another beam splitter 96 which splits the beam into two paths 98and 100. In FIG. 2 the X-coordinate is perpendicular to the paper andconsequently, cylindrical lens 102 is shown with a curvature, while anidentical element 104, in the other path, appears as a plano-parallelelement. The path leading to detector 90 also contains a spherical lens,106. The two identical quadrature detectors 90 and 92 detect across-section of each beam. As the substrate surface position, orthickness, varies, the beam cross section, as seen by the detectors,varies in the X-direction as shown in FIGS. 5 and 6 at 108, 110 and 108,112 respectively. It is to be noted that on neither detector does thevertical (Y-direction) diameter of the illuminated area change. When themask is in focus, both detectors are illuminated by a circular beam 108.As the mask goes out of focus, the horizontal diameter shrinks on onedetector (see FIG. 5), while on the other one it increases (see FIG. 6)as indicated by the outlines of the beam 110 and 112, respectively. Thischanges the electrical output from the quadrature detectors. The focuscorrection signal F_(c) is then: ##EQU1## where A₁ is the signal derivedfrom quadrants along the X axis of 90,

A₂ is the signal derived from quadrants along the X axis of 92,

B₁ is the signal derived from quadrants along the Y axis of 90,

B₂ is the signal derived from quadrants along the Y axis of 92.

Transmitted Light Inspection Mode

Ordinarily, transmission mode detection is used for defect detection onsubstrates such as conventional optical masks having transparent areasand opaque areas. As the laser beam scans the mask, the light penetratesthe mask at transparent points and is detected by transmitted lightdetector 34 which is located behind the mask 14 and measures the lightcollected by condenser lens 84 and collector lens 86.

Reflected Light Inspection Mode

Reflected light inspection is normally performed on opaque substratesthat contain image information in the form of developed photoresistfeatures. Light reflected by the substrate passes backwards along thesame optical path as described before but is then diverted by apolarizing beam splitter 60 into detector 36. A condenser lens 35projects the light onto the detector 36. As previously stated, duringreflected light inspection, shutter 63 is closed.

Reflected light inspection may also be used to detect contamination ontop of opaque substrate surfaces.

Phase Shift Material Thickness Measurement Mode

The measurement of phase shift is of interest only at points where thesubstrate is transparent, i.e., where there is no opaque geometry. Thepresence of opaque geometry is detected by the transmission detector 34and only in the spaces separating such geometry is a phase shiftmeasurement taken. During this operation shutter 63 is open and lightfrom the laser reflected by splitter 60 travels through relay lenses 110and 112, which form a telescope 114, and through a low numericalaperture objective lens 116 to a tilted mirror 118 where it is reflectedback along the same path and through beam splitters 60 and 94, andcondenser lens 35 to reflected light detector 36. At the same time,detector 36 is also illuminated by light which first passes throughsplitter 60 to be reflected from a point on the substrate and which onreturning is reflected by splitter 60 to the detector. These twoluminous beams interfere with each other, and the intensity of the lightdetected by detector 36 therefore varies as a function of the relativeoptical path length of the two paths 62 and 64. As will be explained inmore detail later, this data is interpreted by the electronic subsystemto determine variations of thickness of phase shift material covering agiven point on the substrate.

Simultaneous Detection by More than One Type of Detector

It is important to note that transmitted and reflected lightinspections, and the phase shift measurement operation are not mutuallyexclusive in time. Simultaneous transmitted and reflected detection candisclose the existence of an opaque defect sensed by the transmitteddetector while the output of the reflected detector can be used todisclose the type of defect. As an example, either a chrome dot or aparticle is opaque and hence will result in a dark output from thetransmission detector, but reflective chrome defects also produce a highreflected light indication while a particle will typically reflect less.By using both reflected and transmitted detection one may locate aparticle on top of chrome geometry. In general, one may determinesignatures for certain types of defects, such as the ratio of theirreflected and transmitted light intensities. This information can thenbe used to automatically classify defects.

Similarly, transmitted light detection and phase shift measurement canoccur simultaneously. On a phase shift mask an opaque defect in a regioncovered by phase-shift material can be detected, and the absence ofopaque material detected by the transmitted light detector 34 can beused to gate the phase shift measurement.

Control Computer

The control computer, 24, acts as the operator console and mastercontroller of the system and is a device such as a SPARC computer madeby Sun Microsystems of Mountain View, Calif. All system interfaces withthe operator and the user's facilities are made through the controlcomputer. Commands are issued to and status is monitored from all othersubsystems so as to facilitate completion of the operator assignedtasks.

Electronics Subsystem

The function of the electronics subsystem 20 is to interpret and executethe commands issued by control computer 24. These functions are:digitize the input from detectors 34 and 36; compensate these readingsfor variations in the incident light intensity; detect defects in theimage and transfer the defect data to the control computer 24;accumulate the output of the interferometers used to track the stage 12;provide the drive for the stages linear motors; and monitor sensorswhich indicate status.

Except for the measurement of phase shift and line width information,all of the enumerated functions of control computer 24 and subsystem 20have been described in the above-mentioned U.S. Pat. Nos. 4,247,203,4,579,455, 4,633,504, 4,805,123, 4,926,489, and 4,644,172. It is to benoted that in the above patents the same functions are performed in manydifferent ways and the particular approach adopted depended on theavailability and suitability of integrated circuit devices at the timethe system was being developed. Any of the cited approaches could beused.

The Stage

The stage 18 is an air-bearing X-Y stage that is driven by a linearmotor on each axis. The position of the stage along each axis ismonitored by interferometers (not shown), such as the Model TIPS V, madeby Teletrac Corporation.

Stage 18 is shown in detail in FIG. 7 with the front rail cut away topermit view of the principle elements. The stage has two degrees offreedom; it has no rotational capability. It is disclosed here forapplication in the described inspection system but could also be used inmicrolithography and any precision machining application.

The Y carriage 120, in the shape of a frame 122, carries the X stage124. The motion of both stages is controlled by linear motors and airbearings. The attractive force between the stator and the slider of eachlinear motor provides the preload of the linear bearings.

The Y carriage frame includes two guideways 126 and 127, controlling themotion of the X stage 124 inside the carriage. The guideways areconnected by two side rails 128. (The front rail, the equivalent of 128,is not shown.) The stator 129 of the X linear motor is imbedded insidethe X guideway 126 in such a way that it attracts the X slider 130attached to air-bearing housings 131 and preloads four of the five X airbearings 132, 133, 134 and 135. A separate magnet 136 and ferromagneticpreload strip 137 provide the preload to air bearing 138. Each bearingis equipped with a swivel, enabling rotation of the bearing pad abouttwo axes, in addition to rotating the bearing itself, thus the onlydegree of freedom constrained by an air bearing is the translation inthe direction normal to the pad surface.

The X stage carries the specimen 14 and is kinematically constrained bythe five air bearings: the bearings 132 and 135 control the pitch of theX stage motion, and constrain the vertical translation in the Zdirection, bearings 133 and 134 control the yaw of the X motion andconstrain the horizontal translation in the Y direction. Bearing 138nested in the housing 139 controls the roll of the X stage andconstrains vertical translation of the stage in the Z direction. Thespecimen holder assembly 140 is attached to a lightweight compositeframe 141 of the X stage.

The stage contains a number of novel features. One such feature is theuse of the linear motor to preload the stage in two directions andthereby achieve an exceptional stiffness. This is accomplished by thearrangement of triangular cross section slider iron 130 and angularposition of the stator 131, so that the magnetic attraction force is atan angle to all four air bearings 132, 133, 134 and 135.

Another innovative feature of the design is that the stator 129 oflinear motor is imbedded inside the guideway 126 at an angle to the twowalls of the guideway.

Also novel is the use of honeycomb material, such as Blue Seal, made byHexcell of Dublin, California, for the construction of frame 140. Thisreduces the mass of the stage, yet makes it very rigid. A cross-sectionof this construction taken along the line 8--8 is shown in FIG. 8 wherecellular insert 142 is sandwiched between skins 143. The bottom plate144 and top plate 145 join the skins 143 and complete the box structureenclosing the insert 142. The honeycomb material may be replaced by anynumber of light composite materials, such as Duocell, manufactured byERG of Oakland, Calif.

Also novel is the method of attaching the solid pieces 146 to thecomposite in the way that they penetrate one skin of the composite walland are attached to the opposite skin and either of the top or bottomplates, as shown in FIG. 9, with joints 147 formed around thepenetration through the wall, and between the solid piece and the insideof the opposite skin and the plate 144.

Operation of the Disclosed Embodiment Alignment

Prior to starting the automatic inspection operation, the operatoraligns the mask in the proper orientation and defines to the computerthe "care area", i.e., the area to be inspected. FIG. 3 illustrates thedesired orientation of the inspection path 31 with respect to dice 33,35, and 37 shown here on a multi-die mask or reticle 14. Duringinspection, the stage 12 is moved in a serpentine manner, following thepath 31, while the laser beam is deflected parallel to the Y-axis of themask. As stage 12 moves in the X-direction, this Y-axis motion of thelaser beam sweeps out a swath, 39. Ordinarily the axes of mask 14 willnot be parallel to the drive axis of the stage. Therefore, an X or a Ydirectional motion of the stage requires both of the drives of the stageto be driven simultaneously. The first task of the operator is thereforeto define to the system the ratio of the speeds of the major axes of thestage. To accomplish this, the operator chooses two points known to himto lie on the same X-coordinate of the die. He then drives the stage tothese points, while observing the image on image display 22. The systemnotes the location of these points by measuring the travel withinterferometers (not shown) along the drive axes of the stage. Thesemeasurements establish the direction cosines of the stage drive axeswith respect to the X and Y axes of the mask. At this time the doveprism 66 (FIG. 2) is rotated to orient the deflection of the laser beamso that it is perpendicular to the X-directional travel of the stage.Next, the operator designates to the system the care area 41 (FIG. 3) ofthe die, the area to be inspected.

Phase Shift Measurement Calibration

For reasons that will become apparent later, in the phase measurementmode, as the laser spot scans (in the Y-direction), a flat transparentsurface parallel to the plane of the mask, the intensity variessinusoidally, as shown by curve 200 in FIG. 11. Mathematically, theintensity I is:

    I=A sin  (2 πy/w)-D)!+I.sub.o                           (2)

where y is the distance of the pixel in question from the origin, w is aconstant that is a function of the tilt angle of mirror 118, D is thephase shift due to path length change as the result of the thickness ofthe phase shift material, A is the half-amplitude of the intensity, andI_(o) is the intensity offset 204 due to stray light in the optics.These values are all determined during the phase shift measurementcalibration part of the initialization. As the laser scans a flatuniform transparent area of the mask, the intensities at each pictureelement (pixel) are digitized and stored in the computer. Then, I_(o) isthe average value of the intensities over integer cycles, and A can becomputed from:

    A=(I.sub.max -I.sub.o)/2                                   (3)

The value W is the periodicity of the sinusoid.

It is to be noted that I_(o) and A are different for clear and phaseshift material covered areas and therefore must be determined for bothareas. The quantity D is a linear function of the thickness of the phaseshift material and this relationship is determined by calibration on aknown sample containing various thickness phase shift material featuresand remains constant while the system retains dimensional stability.

The Inspection Process

Automatic inspection of a reticle ordinarily starts at the upper lefthand corner of the care area and follows the serpentine pattern 31 (seeFIG. 3). As the stage slowly moves in the X direction, the laser beamrapidly sweeps in the Y-direction. In this manner a swath 39 is scannedand the digitized output of the detectors is stored in the electronicssubsystem 20. When the swath reaches the left boundary of the care areaof the second die 35, image data derived from die 33, and now stored insubsystem 20, is compared with the data derived from die 35. Anysubstantial difference is designated a defect. In a similar manner, thedata from die 37 is also compared with the data derived from die 35.

When the scanning process reaches the right boundary of the care area ofdie 37, the stage is moved in the Y-direction an amount slightly lessthan the swath width and the stage starts a return trace in theX-direction. In this manner the care areas of the dice are traversed bythe serpentine motion.

Die-to-database inspection, ordinarily performed on single die reticles,is similar to die-to-die inspection except that the comparison occursbetween the die and a simulated image generated by database adaptor 18.FIG. 4 illustrates the die-to-database scan path 31'.

Review Operation

After completion of the automatic inspection operations, the operatorreviews the defects by causing control computer 24 to move the stage 12to the area of a particular defect and hold it there. The image is thenscanned by acousto-optic scanners 40 and 42 in the Y-direction and byoscillating mirror 65 in the X-direction, and the digitized image isdisplayed on display 22. The operator may use the output of any of thedetectors or the combination of outputs from more than one detector. Ifthe operator desires, the different detector outputs may be superimposedand represented as separate colors on the display.

Phase Shift Material Thickness Measurement

FIG. 10 is an illustration of the cross section of one type of a phaseshift mask. While the present example relates to a particular type ofmask, on all types of masks, control of the thickness of phase shiftmaterial is a requirement and hence the technique described here isapplicable to all types of phase shift masks.

The substrate 160 is typically of quartz on which opaque features 164are deposited. These are typically thin layers of chrome. Phase shiftfeatures 161 and 162 made of transparent material will typicallypartially overlay part of the chrome 164 and some of the clear areas 181and 183 between the features 164. Phase shift material filledtransparent areas 181, 183 and clear areas 180, 184 typically alternate.The height of the upper surface 173 of the phase shift feature 162 abovethe level of the front, or upper, surface 174 of the quartz substrate istypically such that it produces a phase shift of 180 degrees withrespect to a point 180 in the same plane but not covered by phase shiftmaterial.

Defects in phase shift masks may occur in several ways. There can bedefects in the transparent areas, such as either excess chrome or dirt,or there can be missing chrome in a feature 164. Such defects aredetected by the transmitted light detector 34 (FIG. 2) and are thesubject of previously referenced prior art. The first aspect of thepresent invention is also capable of detecting defects in the phaseshift layer 161 or 162. There are two types of defects: those wherethere is a sudden variation of thickness of the phase shift layer, andthose in which there is a deviation from the desired thickness which iseither constant, or varies slowly over the surface. The former type ofdefect, such as the divot 168 in layer 161, is detected by thetransmitted light detector 34 because it scatters the light and hencedoes not allow the light to pass through the phase shift material. Ittherefore appears as a dark spot in transmission. Slowly varyingsurfaces 172 or incorrect thickness of the phase shift layer, such asdepicted in feature 161, are detected by interferometric methods, asexplained below.

A perfectly flat surface, such as 173 at the top of 162, parallel to theplane of the mask and with an optical path length L will produce fringesas the mask is scanned because, due to the tilted mirror 118, thewavefront of the reference beam is not parallel to the plane of thesubstrate. (In order to avoid any ambiguity in the direction of thechange of the phase, the tilt of mirror 118 should be greater than themaximum expected slope of any surface such as 161.) The detector outputin such a case is a sine wave, such as that shown in FIG. 11. A similarflat surface located at a path length L+d (see FIG. 10) will produce asine wave of the same frequency but with a phase shift D with respect tocurve 200. This second sine wave is shown as wave form 202.

As the mask is scanned in the Y-direction, the transmitted lightdetector 34 detects whether a particular pixel is fully transparent.Only at such fully transparent pixels are reflected light intensitymeasurements taken and digitized. At such pixels, the reflected lightintensity is determined and digitized. This is suggested by thedepiction at the bottom of FIG. 10 wherein it is indicated that duringthe time that the scan is passing across the non-transparent feature164, as determined by the output of detector 34, the output of detector36 is ignored. From the intensity value, and from the Y-coordinate ofthe pixel, together with the values of A, w and I_(o) determined duringthe calibration, electronic subsystem 20 determines D in Equation 2 andthe corresponding path length variation at the pixel, i.e., the height dof the feature surface above plane 174.

It is to be noted that due to the periodic nature of a sinewave, thereis an ambiguity because path length variations corresponding to a phaseshift of 360 degrees are indistinguishable. However, sudden variationsresulting in a 360° phase shift can occur only when the phase shiftmaterial contains a ridge. Such a ridge produces diffraction which isthen detected in the transmission mode. Hence, the ambiguity due to a360° phase shift is resolvable and it is possible to continuously, atevery pixel, track the thickness of the phase shift material.

In practice, the mask substrates are not likely to be perfectly parallelto the image plane, nor is the substrate likely to be perfectly flat.However, these variations are gradual, and on a 5× phase shift mask oneneed consider variations only within a radius of 4-5 microns.Specifically, only the relative phase shift between two adjacentfeatures is important, such as the relative phase shift betweenlocations 180, 162 and 184. These points are likely to be less than 4microns apart.

To determine whether there is a phase error of sufficient magnitude toindicate a defect on the substrate, the path length is computed at eachtransparent pixel covered by phase shift material 162 (FIG. 10). Thisvalue is then compared with the average of the path lengths of twoadjacent points where there is no phase shift material, such as points180 and 184. If the difference in path length differs from an acceptablevalue by more than a predetermined threshold value at the print wavelength, such as 10 degrees for example, the phase shift materialthickness at the inspected point is marked as defective.

In addition to making path length comparisons between points ongeometric features in the same vicinity, the system also checks for amissing or extra geometric feature, such as may occur in the patterngeneration. In die-to-die mode, the path lengths of pixels at 173, 180and 184 (FIG. 10) of the die 33 (FIG. 3) are compared with the pathlengths at the corresponding pixels of die 35. This comparison willdisclose any missing geometric features, unless both dice 33 and 35 havethe same error. Similarly, in die-to-database mode a comparison can bemade between the path lengths associated with the previously designatedpixels and the description of these pixels in the CADs database.

Alternate Phase Shift Measurement Method

The above measurement technique uses a digital approach to determine therelative optical path length at grid points to determine the phase shiftangle at every point. As explained below, one may also employ an analogmethod to find the phase shift angle.

FIG. 12 illustrates the additional circuitry required by this method forinsertion into the apparatus of FIG. 1 at 208 to determine the phaseshift angle. The analog signal derived from detector 36 is fed to oneinput 209 of an analog phase detector 210 which also obtains anothersignal at 211 from a numerically controlled oscillator 212. A signalproportional to the phase difference between these two signals isconverted to a digital form by an eight bit A/D converter 214 and passedto an encoder 216 and also to a digital low pass filter 218. The digitalfilter 218 and the encoder 216 are gated by a gating signal derived fromdetector 34. The digital filter 218, which functions as an integrator,accepts an input only when detector 34 indicates that the mask istransparent at the inspected point. Encoder 216 accepts the 8-bit outputsignal of the A/D converter 214 and shifts it right one bit. If thepixel is transparent at that point, the encoder inserts a 0 into themost significant position of the digital signal and transmits theremaining signal to subsystem 20 as the phase signal. Should detector 34indicate that the pixel is opaque, the digital signal will be encoded asall ones, 11111111. This signifies to the subsystem 20 that the phasesignal is invalid and should be disregarded.

The previously explained circuitry is a phase-locked-loop that followsslow variations of the phase, as might be caused by slowly varyingphenomena, such as imperfect flatness of the mask. The output of theencoder 216, when valid, indicates the path length variation in thelocal area.

Alternate Phase Shift Optical System Implementation

In some instances it is desirable to measure the actual phase shift,rather than infer the phase shift from the relative path length. Thismay be done by using transmitted interferometry. FIGS. 13a and 13b aresimplified schematic diagrams, in which for simplicity many of theelements shown in FIG. 2 are omitted, but illustrate a variation of thepreferred embodiment that permits measurement in either or both atransmit mode or a reflected mode using respectively transmitted lightinterferometry and simultaneous measurement of the reflected andtransmitted interference pattern.

As depicted in FIG. 13a, to implement this alternative operating in thetransmit mode, a pellicle beam splitter 230 is added which reflectslight received from splitter 60 and produces a reference beam atdetector 34 via the path 231 past tilted mirror 232, objective lens 234and another beam splitter 236. The interference of the reference beamand the imaging beam passing along path 240 and through substrate 14 isdetected at detector 34.

In the reflected light mode, reference light split by splitter 60 isdirected along the path 250 to tilted mirror 118 and returned todetector 36 where it interferes with imaging light passing throughsplitter 60 and along the path 260 to substrate 20 where it is reflectedback along path 260 and reflected by splitter 60 into detector 36.

It is to be noted that this alternative also permits the simultaneousmeasurement of the phase in both the reflected and transmitted modes.

Because lasers have a limited coherence length in both the reflected andtransmitted interference modes, the path length should be approximatelythe same for the imaging beam path and the reference beam path.

Line Width Measurement

FIG. 14 shows a plan view of a small portion 270 of a mask. Area 272 istransparent and is crossed by a feature 274 that may either be opaque(chrome or other material) or transparent if the quartz substrate of themask is covered by phase shift material. The system measures theintensity at equidistant grid points, depicted at 276. As explained morefully below, these intensity measurements are then used to determine theline width, i.e., the distance 278 across feature 274.

It is to be noted that at each of the grid points 276 the intensity isthe convolution of the point spread function of the optical system withthe transmissivity profile of the feature. Typically, the transmissivityprofile is a step function. Therefore, for a straight feature, as isshown in FIG. 14, the intensity measured at a particular grid point is afunction of the perpendicular distance from the grid point to the edgeof the feature (line 274). The intensity at a particular point in thevicinity of a feature can thus be interpreted as the perpendiculardistance from the point to the line. This interpretation is done in asimple table look-up operation in the computer 24 (FIG. 1). On the basisof the intensities at grid points 280 and 282, distances S₁ and S₂ areknown and the slope of the edge relative to a feature is: ##EQU2## wherea is the distance between the grid points 280 and 282 and G is angle284.

Once the slope of the edge of a feature (line) has been determined, theopposite edge of the line can be similarly located, and a verificationcan be made that it is parallel to the previously calculated line edge.On the basis of the intensities along the two edges of the line, thelinewidth is calculated in control computer 24.

The previously described method of line measurement is, strictlyspeaking, normally applicable only to conventional masks which have nosurface areas covered by phase shift material. However, the techniquedescribed above may also be used for the measurement of phase shiftfeatures because, at the boundary between a clear area and an areacovered by phase shift material, diffraction of the incident light beamwill occur and along this narrow boundary no light will be transmitted.The line width is the distance between the center of one boundary andthe center of the opposite boundary.

Although the first aspect of the present invention has been describedabove in terms of preferred embodiments, it is anticipated that variousalterations and modifications thereof will be apparent to those skilledin the art. For example, to avoid the need to sweep the laser beamduring the scanning operation, instead of using the linear detector 34in the preferred embodiment, one could use a time delay integratingsensor of the type described in the above-referenced Levy U.S. Pat. No.4,579,455. With such modification, if a laser is used as the lightsource, coherence in the Y-direction would have to be destroyed by usinga rotating ground glass. The coherence in the X-direction is destroyedby the time delay integrating sensor. It is therefore intended that thefollowing claims be interpreted as covering all such alterations andmodifications as fall within the true spirit and scope of the invention.

SECOND ASPECT OF THE PRESENT INVENTION

The second aspect of the present invention, as will be seen from thefollowing discussion, provides an inspection system and method thatrepresents a major departure from the traditional die-to-die comparisonmethod of substrate inspection. With the well known and widely useddie-to-die (or die-to-data base) comparison technique, thecharacteristics of the substrate under inspection are compared toanother like substrate or a data base that is known to be correct. Thatrequires the simultaneous processing of the same information with twooptical columns for the die-to-die for both the die under inspection andthe sample to which it is being compared which is both hardware andcomputer processing intensive.

As will be seen in the discussion that follows, the second aspect of thepresent invention performs all of the inspection tasks using only asingle optical column and only the substrate to be inspected. This, aswill be seen, is accomplished by analyzing the relationship between twoor more of the transmitted and reflected light signals from thatsubstrate and derived functions of those signals, the relationshipbetween those light signals, and the relationship between each of thetransmitted and reflected light signals and the second derivatives ofthose light signals.

System Overview

Before fully explaining the theory and operation of the second aspect ofthe present invention and all of the options that it presents, the basicstructure of the system of the second aspect of the present invention,as shown in the simplified view of FIG. 15 and the more complete view ofFIG. 16, is very similar to the simplified and detailed FIGS. 1 and 2,respectively, for the first aspect of the present invention. Thedifference between FIG. 1 and FIG. 15 is that data base adaptor 18 isnot needed for the second aspect of the present invention. Similarly,the difference between FIGS. 2 and 16 is that the phase shift/line widthmeasuring components that extend to the left from beamsplitter 60 arenot necessary to perform the function of the second aspect of thepresent invention. However, the phase shift/line width measurementscould be performed using the same transmission data as that used forinspection by the technique of the second aspect of the presentinvention. From FIGS. 15 and 16 it can be seen that the automaticoptical inspection system 10 includes three specialized subsystems: alaser/optical subsystem 11; an x-y stage and servo drives 12 subsystem;and an electronics control and display subsystem 19. FIG. 15 also showsa substrate 14 on X-Y stage 12 that is to be inspected for defects.

It is important to note that transmitted and reflected light inspectionscan be performed either simultaneously or mutually exclusively in timewith the requirements for the illumination light beam on, and theposition of, substrate 14 being as discussed above.

Briefly, the underlying theory of operation, which is discussed morecompletely below, relies on the ability of the comparison of signalsthat correspond to at least two of the detected transmitted andreflected light beams and functions of each of them being able todisclose the existence of a defect. The two measured values of thesystem are the intensity of the light beam transmitted through thesubstrate as sensed by transmission detector 34, and the intensity ofthe reflected light beam as detected by reflected light detector 36.Those two measured values can then be processed to disclose the type ofdefect, if any, at a corresponding point on the substrate. As anexample, either a chrome dot or a particle on a substrate is opaque andhence will result in a "dark output" (low signal output) fromtransmission detector 34, with the reflective chrome dot defect on thesubstrate producing a high reflected light indication while the particlewill typically reflect less. Thus, the use of both reflective andtransmissive detection, for example, one may locate a particle on top ofchrome geometry which could not be done if only the reflective ortransmissive characteristic of the defect was examined. In general, onemay determine signatures for certain types of defects, such as the ratioof their reflected and transmitted light intensities. This informationcan then be used to automatically classify defects.

X-Y Stage and Servo Drives 12

X-Y stage 12 is a precision substrate driver under control of electronicsubsystem 20 and capable of moving substrate 14 under test in aserpentine fashion, within a single plane, relative to the optical axesof optical subsystem 11 so that all, or any selected part of, thesubstrate surface may be illuminated and therefore inspected.

In a typical inspection system of the second aspect of the presentinvention, stage 12 is an air-bearing X-Y stage that is driven by alinear motor, or servo, on each axis with the position of stage 12 alongeach axis monitored by interferometers (not shown), such as a model TIPSV, made by Telectrac Corporation.

Electronics and Control Subsystem 19

The electronics and control subsystem 19 includes several elements asshown in FIG. 1. Included are electronic subsystem 20, control computer24, keyboard 26 and display 22. Keyboard 26, in communication withcontrol computer 24, and display 22, in communication with electronicsubsystem 20, provide the user interface to the inspection system of thesecond aspect of the present invention. Additionally, electronicsubsystem 20 is in communication with x-y stage 12, transmission andreflected light detectors 34 and 36, and control computer 24.

Control computer 24 acts as the operator console and master controllerof the system and is a device such as a SPARC computer made by SunMicrosystems of Mountain View, Calif. with all system interfaces withthe operator and the user's facilities made through control computer 24.Commands are issued to and status is monitored from all other subsystemsand components so as to facilitate completion of the operator assignedtasks.

The function of electronics subsystem 20 is to interpret and execute thecommands issued by control computer 24. These functions are: digitizethe input from transmission and reflected light detectors 34 and 36;compensate these readings for variations in the incident lightintensity; accumulate the output of the interferometers used to trackthe stage 12; provide the drive for the servos of stage 12; and monitorsensors which indicate status.

Operational Theory

Transmission detector 34, instantaneously and continuously, generates atransmitted light signal 15 in proportion to the light transmittedthrough substrate 14 and received by transmission detector 34.Transmitted light signal 15 is then amplified and offset in electronicsubsystem 20 to normalize the peak-to-peak signal amplitude to values of0 to 1. Similarly reflected light detector 36, instantaneously andcontinuously, generates a reflected light signal 17 in proportion to thelight reflected from substrate 14 and received by reflected lightdetector 36. Reflected light signal 17 is similarly normalized inelectronic subsystem 20.

For purposes of discussion and to further discuss the second aspect ofthe present invention, substrate 14 is assumed to have an opaque layerthat covers a portion of the underlying material of substrate 14. Thatopaque layer will reflect a greater portion of incident laser light 13than is similarly reflected from the surface of the bare underlyingmaterial of the substrate. For example, it is known in the art that, ata wavelength of 488 nm, anti-reflective chrome (opaque layer) has areflectance of 11% and quartz underlying material of a substrate has areflectance of 4.5%.

FIG. 17 illustrates a hypothetical model for the normalized transmittedand reflected light signals 350 and 352, respectively, for a scan acrossa substrate with the abscissa of FIG. 17 being time, or distance acrosssubstrate 14, as light beam 13 is advanced relative to the surface ofsubstrate 14. When light beam 13 scans a bare section of substrate 14having a quartz underlying material, the normalized transmitted lightsignal 350 is at level 1 and the normalized reflected light signal 352is at level 0, as shown in region 340 of FIG. 17. Further, when lightbeam 13 scans a region of substrate 14 having an opaque layer, thenormalized transmitted light signal 350 is at level 0 and the reflectedlight signal 352 is at level 1 as shown in region 342 in FIG. 17. In thecase where light beam 13 is at an edge of an opaque layer, or feature,on substrate 14, the normalized transmitted light signal 350 transitionsfrom level 1 to level 0 while the normalized reflected light signaltransitions from level 0 to level 1 as illustrated in region 341 of FIG.17.

This hypothetical model assumes that the transmitted and reflectedsignals at the same point on substrate 14 are always complementary toeach other in the absence of defects, so that their sum 354 is alsoinvariant in the absence of defects. This behavior is represented inFIG. 17 by summation signal 354, which is offset by 0.5 from each ofsignals 350 and 352. Thus, such behavior would allow any observeddeviation in the summation signal to be interpreted as a defectdetection. The next paragraph discusses some shortcomings of thishypothetical model and proposes a method for the detection of defectswhere this approach could be strengthened. The following discussionprovides an approach that is unconstrained by the shortcomings of themodel just discussed.

Referring now to FIG. 18 the typical signals observed for a realizableoptical subsystem are illustrated in a manner similar to that of FIG.17. Included are transmitted light signal 370, reflected light signal372, and summation signal 374 offset by 0.5 in the left most region thatcorresponds to region 340 of FIG. 17. In that region of FIG. 18 thesignal values are typical for inspection over the clear substrate withno opaque over-layer or defects present. In the center region of FIG.18, a blip 373 in the normalized reflected light signal 372 and aresultant blip 376 in the summation signal 374 both result from aparticulate contamination on top of an opaque layer on substrate 14. Inthe right most region of FIG. 18, blip 371 in the normalized transmittedlight signal 370, the corresponding blip 375 in the normalized reflectedlight signal 372, and resultant blip 377 in the summation signal 374 allare caused by a particulate contamination on a transparent substrate 14.

Also note that in the typical situation, summation signal 374 alsodeviates from the constant 0.5 level in the transition regions (similarto regions 341 in FIG. 17) of the plot. These transition regionscorrespond to those portions of substrate 14 that are near the edges offeatures thereon (e.g. boundaries between opaque layers on the substrateand bare underlying substrate regions). Such a deviation appears in FIG.18 as blip 378. Deviations such as blip 378 are due to variations in thelight scattering behavior at edges of features on substrate 14, andmismatches between the partial coherence parameters of the transmittedand reflected optical paths (see FIGS. 15 and 16). Typically thesedeviations in the summation signal at feature edges can be of roughlythe same size as a blip 377 caused by submicron contamination onsubstrate 14. Therefore, detection of defects by the summation of thereflected and transmitted light signals 17 and 15, respectively, doesnot provide an adequate method for distinguishing submicron particulatecontamination from feature edges on substrate 14.

An extension of the method to enable a realizable optical subsystem toautomatically distinguish between surface features and defects of asubstrate 14 is discussed below in relation to FIGS. 19-22.

FIG. 19 illustrates the relationship between a family of pairs ofnormalized transmitted and reflected signal values with each pair ofvalues occurring at a particular point on the surface of substrate 14 aslight beam 13 is deflected over substrate 14, showing the correlationbetween each of the two signal pairs with no defects present at anypoint on substrate 14. In FIG. 19 the normalized transmitted lightsignal is plotted on abscissa 400 and the normalized reflected lightsignal from the same point on substrate 14, is plotted on ordinate 401for each pair of signals from each inspected point on substrate 14.

As discussed above in relation to FIG. 15, electronic subsystem 20normalizes and offsets the transmission and reflected signals 15 and 17to range between 0 and 1. Thus, for example, region 450 of FIG. 19represents signal pairs from a substrate region where there is a muchgreater reflected signal than transmitted signal which could representan opaque layer on the substrate at that point. This results since anopaque layer attenuates the light beam resulting in a small lighttransmission value, and at the same time, that opaque layer reflectsapproximately 11% of the incident laser beam to reflected light sensor36. Similarly, region 452 of FIG. 19 can be seen to represent thecondition where laser beam 13 scans a bare region of a quartz substrate.Values in region 452 result from a point on substrate 14 that transmitsa large portion of light beam 13 resulting in a high detectedtransmitted light value, while at the same point on the substrate onlyabout 4.5% of the incident laser beam 13 is reflected resulting in asmall detected reflectance value. Thus, the intermediate region 455 inFIG. 19 represents points on the surface of substrate 14 where lightbeam 13 is scanning the edges of features.

A typical transmission-reflection relationship in T-R space (thecoordinate plane defined by T and R orthogonal axes) for a realizableoptical system is shown by curve 420 enclosed within a uniform tolerancearea defined by envelope 421. (Note that the shape of curve 420 willvary depending on several factors: the operational characteristics ofoptical subsystem 11; as well as the materials of the underlying layerand surface layers of the features of substrate 14. Each combination ofoptical subsystem and substrate design therefore will have its owncharacteristic curve 420 in the T-R space.)

Thus, each inspectable point, or pixel, on substrate 14 can berepresented in the T-R space by a point with coordinates correspondingto the transmitted and reflected signal values produced at that pixel.Those pixels with transmitted and reflected signal values which fallwithin tolerance envelope 421 are considered to be defect free while allothers represent either defects or system noise. The tolerance to whichthe inspection is to be performed, and hence which transmitted andreflected pixel pairs will be considered defective, is determined by thewidth of envelope 421 and the distance of its boundary from curve 420.The width of envelope 421, and hence the inspection tolerance, can bevaried parametrically by position along curve 420 so that a user mayestablish a tighter tolerance against more harmful types of defects anda more relaxed tolerance against other types of defects. For example,the defect identification sensitivity over bare areas of the substratecan be independent from the identification sensitivity of defects overthe opaque areas of the substrate. One could even have a complex set oftolerances that span the entire T-R space (i.e. the width of envelope421 does not have to be uniform along T-R curve 420).

Thus, one feature of the second aspect of the present invention is a T-Rspace coordinate plane as in FIG. 19. Thus, if the T-R point for anypoint from substrate 14 falls outside the selected tolerance envelopedefined by boundary 421, a defect is identified whether or not theactual coordinates of the point of the defect are known. Keep in mindthat there has as yet been no discussion in this section of thespecification of the alignment of the substrate and the maintenance ofany coordinates of defects in memory. Since the present inspectionsystem is not a comparison system, as in the prior art, it is notnecessary to know the physical location of a defect on the substrate todetermine that there is a defect. All one needs to do is to select thetolerance that is acceptable for each type of surface characteristic andif a T-R measurement falls outside of envelope 421 the substrate isdefective. It should also be kept in mind that it is also not importantto the method of the second aspect of the present invention that thepoints in the T-R space be contiguous for the method to find defects.For example, the first point may fall in region 450, the next 55 pointswithin region 425, then 6 points in region 450 again, one point inregion 455 and then 2 points in region 452, etc. The sequence isunimportant to the ability of the second aspect of the present inventionto identify the presence of a defect.

Also, as discovered during the development of the second aspect of thepresent invention, the location of the T-R point in the T-R plane alsoconveys information about the physical properties of the pixel elementon the surface of the substrate and, in the case of a defect, the typeof defect found. Thus another feature of the second aspect of thepresent invention is the use of the T-R detection space for automaticdefect classification.

Given that discovery, the defect detection process of the second aspectof the present invention includes at least the ability to identifydefect types using T-R space. To do so, the non-defective region in T-Rspace defined by boundary 421 must be determined so that any T-R pairfor an inspected pixel on substrate 14 can be instantly determined as adefect or a non-defect point by whether it falls inside or outside thenon-defective region within boundary 421. Furthermore, the location ofthe T-R point could, if desired, be analyzed to identify the type ofdefect that was detected.

Methods for bounding the non-defective region and the various defectclassification zones, collectively referred to as the T-R reference map,are discussed further below. Additionally, since the defect detectionprocess depends only on the two measured signals, T and R, at a singlepoint of the substrate, and does not depend upon the comparison of testand reference images (die-to-die or die-to-data base) as taught in U.S.Pat. No. 4,926,489, no alignment of the substrate with the defectdetermination system of the second aspect of the present invention isrequired.

With that said, it has been observed that the use of a global alignmentstep of the substrate to a reference grid would further enable thesystem to determine the location of the defect on substrate 14 as well,if the user should so desire. However, as stated above, for a pass/faildefect determination test the physical location on the substrate of thedefect is unnecessary.

FIG. 20 is a plot of a typical T-R reference map that illustratesvarious defect regions which one might encounter with the type ofsubstrates currently of interest. For example: particulate contaminationon anti-reflective chrome would have low T values and intermediate Rvalues as represented by region 470; particulate contamination on anotherwise bare quartz region would have low R values and intermediate tohigh T values as represented by region 474; particulate contamination onthe edge of a feature could have a broad range of T and R values fromboth being low to one being high while the other remains low asrepresented by region 472; a missing anti-reflective chromium layerwould have a high R value and a low T value as represented by region478; very large defects would have very low values of T and R asrepresented by region 480; and the presence of thin residual chrometransmission defects would have T and R values that are to the right andabove characteristic curve 420 as represented by region 481.

For some types of defects, analysis of the T-R point may not be asensitive enough indication of the presence of a defect (i.e. thevariation of either the T or R value may not be sufficiently indicativeof a problem given the corresponding other value for a particular pixelon substrate 14). An example of this type of defect is an inclusion in aquartz substrate, wholly contained below the surface of a mask. In thattype of defect the change of the transmission value, T, occurs withlittle or no corresponding change in the reflectance value, R. As can beseen from FIG. 20, nominal reference curve 420 has a small slope forlarge T values. Therefore a change in the transmission value alone inthis region may not result in a T-R point outside envelope 421 and hencewill be difficult to detect, or go undetected, in T-R space alone.

However, if the second derivative of the normalized transmission value,T", which identifies the presence of edges in the image, is plottedagainst the normalized transmission signal, T, as in FIG. 21, thosetypes of defects can be identified. The nominal behavior for pixels fromdefect-free points on the substrate correspond to the curve 503,enclosed by tolerance envelope 506 as shown in FIG. 21. The coordinateplane such as in FIG. 21 is referred to as the T-T" detection space, andis another feature of the second aspect of the present invention.

As with T-R space, T-T" reference map is derived by identification ofthe defect-free region, here within envelope 506, and other specificregions of interest in T-T" space. In this case, a change intransmission, resulting in a T-T" point within locus 520, outside thenon-defective region in envelope 506, tentatively indicates atransmissivity defect, although such a point could occur when the pixelis located near the edge of a feature and not be a defect at all. Thus,T-T" space alone could not be relied on to make the necessarydistinction in such a situation. A test for this condition is explainedin the next paragraph.

During the development of the second aspect of the present invention, ithas also been discovered that it is useful to examine the reflectedsignal, R, plotted against the second derivative of the reflectedsignal, R". FIG. 22 similarly illustrates the R-R" space which is also afeature of the second aspect of the present invention. Curve 603represents the nominal relationship between R and R", and region 607represents the region of tolerance for non-defective pixels with theR-R" detection space also divided into distinct regions of interest. Oneof those regions of interest includes the tentative defect-free regionwithin curve 607, to form an R-R" reference map. Other regions ofinterest include locus 605 with the points therein potentially resultingfrom the laser scanning an opaque layer where the R value is high, the Tvalue low, and the value of R" is also low. Another region of interestis within locus 609 where points therein tentatively result when thelaser scanning beam illuminates a point on a bare substrate. The thirdregion of interest is the locus of points 630 which is typical of anilluminated pixel that is not positioned on the edge of a feature whenthere is a corresponding reading of that pixel in region 520 of the T-T"space (FIG. 21). With both of those conditions being met, the pixel ofinterest corresponds to a transmissivity defect on the sample. Finally,where there is a residue on an opaque layer, associated pixels in R-R"space will be in region 620, with the corresponding values of R and R"signifying the presence of a reflectivity defect.

Thus, to positively identify and classify all possible types of defectsof today's substrate materials at a point on a substrate, it isnecessary to determine which defect regions are occupied by thecoordinates of the point in each of the T-R, T-T", and R-R" spaces. Withthat information, electronic subsystem 20 can reduce coordinateinformation into region information and generate an independent defectregion report for each space with a code to indicate the region (e.g.452, 455, 470, 472, 474, 478, 480, 481, 505, 507, 509, 520, 605, 607,620, 630, etc.) occupied by the coordinate in that space. Further, withsuch a region report available from each detection space, electronicsubsystem 20 can then logically merge the region reports from each ofthe detection spaces to synthesize a final defect report thatcomprehensively encodes the results collected for that point on thesubstrate and reports whether a defect was indicated by those results.That final defect report would thus indicate a pixel type code and abinary defect indicator value that indicates whether or not a defect ispresent. With this information at hand, the system can also beprogrammed to produce other types of reports, including one that totalsthe number of points having each type of defect over the entiresubstrate.

Many defect types can be found simply by the occurrence of a defectindication falling within the coordinates of a defect detection regionin only one of the two function spaces (i.e. T-R, T-T" or R-R" space).However, as explained above, for example, certain transmissivity defectscan only be detected by an occurrence of a defect indication in both theT-T" space in region 520 (FIG. 21) that corresponds to a defectindication in R-R" space in region 630 (FIG. 22). In those instances, afinal transmissivity defect report is generated only if those defectoccurrences are indicated by both region reports in the two differentspaces. That type of report is generated by a logical AND operation thatdetermines if the T-T" space reports a coordinate in region 520 AND theR-R" space also reports a coordinate in region 630. Positiveverification of both occurrences then produces a final report thatindicates the presence of that type of transmissivity defect.

Thus, the final defect detection and classification procedure is carriedout by merging the various region reports. Some types of defects may beconditional on multiple reports, such as the transmissivity defectdiscussed above, while other types of defects may be unconditionallyindicated by single individual reports. Looked at from a hyperspaceperspective what is being said is that some defects can be determined intwo dimensional space (e.g. T-R, or T-T", or R-R" space individually,that is from a single report as described above), while others can onlybe determined in three dimensional space (e.g. T-R-T"), and yet othersmay require four dimensional space, or five dimensional space, etc.

Electronic subsystem 20 is thus programmed to perform the necessarycombinations of logical operations in the required order to generate afinal defect report that identifies the defects of interest from thecollected region defect reports. The final defect report is generated byfirst combining all the conditional reports by AND operations in theproper sequence, and then ORing those results with the other reportswith the final defect report thus indicating a defect if any of theindividual region reports indicate a defect, by either conditional orunconditional detection (i.e. from two, three, four, five, . . . spacein the hyperspace model), and provides a defect type code that indicateswhich regions from the defect region reports were responsible fordetermining the presence of the defect.

In practice, given the materials of current interest, the various defecttypes are detected by fusion of the analytic results obtained from thethree individual detection spaces, which involve the four pixelobservables T, R, T", and R", which have been discussed above as beingplotted pairwise in three individual two-dimensional coordinate planesto simplify the initial consideration of the method of the second aspectof the present invention. In reality, the defect detection process ofthe second aspect of the present invention occurs within afour-dimensional observation hyperspace with coordinate axes T, R, T",and R", with the four observables from each pixel forming afour-component vector. Additionally, this hyperspace can be subdividedinto various hyperdimensional classification regions as illustrated inFIGS. 20-22, and even T-R", R-T" and T"-R" spaces, if for somematerial/defect combination those spaces would also be of interest inthe resolution of whether a particular type of defect is present thatcan not be determined from one or more of the previously discussedspaces. Since the nominal defect-free behavior of an inspected substratewill contain a high degree of correlation in this four dimensionalhyperspace, the second aspect of the present invention takes advantageof this redundancy by analyzing the observables in pairs, projecting theobservable four-vectors onto selected two-dimensional coordinatesubplanes, essentially decomposing the four-dimensional observationspace into three individual two-dimensional subspaces for simplervisualization, calculation and identification of defect types.

Thus, it is easy to visualize that alternate embodiments of the secondaspect of the present invention might effectively utilize other possiblecombinations of the four observables for detection analysis, T versus R"for example. Furthermore, such alternate subspaces need not be limitedto two-dimensional projections of the observables, and in principle mayextend to utilization of the entire four-dimensional representation fordetection analysis as inferentially discussed above.

Furthermore, other observables might be generated by performingalternative filtering operations on the measured T and R signals asrepresented by the block diagram of FIG. 24. For example, the measured Tand R signals and additional high-order signals derived from themeasured signals to create image maps. Thus, in addition to the secondderivative functions as discussed above, larger convolution operatorswith unique coefficient values might also be used to produce othersignals to analyze to more clearly reveal other characteristics of asubstrate of interest. In general, given an arbitrary number ofobservables (e.g. derivatives of various levels, signal rangelimitations of which selected derivatives may be taken, integrations, orany other type of function that can be generated from the measured T andR signal values), they may be analyzed within an arbitrary number ofsubspaces of the observation space, of arbitrary dimensionality lessthan or equal to the number of observables (two to n dimensional space).As already discussed above, comprehensive defect detection usinglower-dimensional subspaces of the observation space generally requiresthat all the information from all reporting subspaces be collected andmerged for final evaluation.

FIG. 24, more specifically, illustrates a general case for performing Moperations on the actual T signal 700 and N operations on the actualreflected signal 702 from the transmission and reflected pixel image mapof the surface being inspected. Each of those various operations in thefirst tier of blocks are identified by a series of filters identified asf_(x) (T) or g_(y) (R). For the process described above, filters f₁ (T)704 and g₁ (R) 706 are each all pass filters, and filters f₂ (T) 708 andg₂ (R) 710 are each second derivative filters to form the signals T" andR", respectively, from the input T and R signals. The other filters thatmight be included in the first tier of operations are illustrated hereas f_(M) (T) 712 and g_(N) (R) 714 which may perform another function onthe input T and R signals to form other signals that would be useful toidentify another feature of interest on substrate 14.

The second tier of operations in FIG. 24 is the combination of thevarious signals from the first tier filters in two dimensional space ofeach possible combination, or at least those of interest, of the signalsfrom the first tier filters. For example, if f₁ (T) 704 and g₁ (R) 706are each all pass filters, and filters f₂ (T) 708 and g₂ (R) 710 areeach second derivative filters, then in block 716 the T-R spaceinformation would be collected, in block 718 the T-T" space informationis collected, in block 720 the R-R" space information is collected, inblock 722 the T-R" space information is collected, in block 724 the R-T"space information is collected, and in block 726 the T"-R" informationis collected. The other blocks in this level illustrate the collectionof other combinations of signals to present the values of those signalsin the corresponding two dimensional space. Then the results of each ofthe blocks in the second tier are provided to the third tier whichconsists of a logical defect merge function 728. The logical defectmerge function 728 could be implemented with a micro-processor that isprogrammed to identify values of the signal pairs in each of the blocksof the second tier that represent a particular defect, and then toprepare a comprehensive defect report of all of the defects that wererevealed by each of the signal pairs of the various blocks in the secondtier.

Computation of the Second Derivative

Here the computation of the second derivatives from the T and R signalsare discussed. Although this transformation is not a point operationfunction, a local neighborhood of pixels adjacent to the pixel inquestion is the only requisite of image integrity for computation andanalysis of the second derivative. It is to be noted that all featuresof the second aspect of the present invention involve the reduction ofreference data to a coordinate-free statistical representation. Thereference map does not contain information about the expected substratebehavior at any specific location, but rather represents the statisticalbehavior at some point on the substrate with the entire substrate, orregion of interest of the substrate, being inspected.

It is again noted that the second aspect of the present invention has norequirement for direct comparison between test images and referenceimages, whether from an adjacent identical lithographic pattern or CADdatabase, and hence an alignment system is still not required.

Prior to discussing the second derivative method in particular,attention is directed to FIG. 23a where a pixelized transmission valueimage of the region of interest of a substrate 14 is illustrated. Forpurposes of discussion the image is shown as a matrix of individualpixel transmission values, t_(x),y, for an image that is n×m pixels insize. It should also be noted, that a pixelized reflection value imagewould be similar and of the same size for the same region of interest ofsubstrate 14. Such a reflection value image can be visualized byreplacing the variable "t" in FIG. 23a with an "r".

The purpose of the second derivative computation is to provideinformation about the proximity to an edge of a feature or defect. Thesecond derivative computation is a linear convolution operation on thegiven image. At every pixel in the image (e.g. t_(x),y in FIG. 23a), alocal rectangular neighborhood of pixels, with the current pixel at thecenter (e.g. for a 3×3 operation

    t.sub.x-1,y-1 t.sub.x-1,y t.sub.x-1,y+1

    t.sub.x,y-1 t.sub.x,y t.sub.x,y+1

in FIG. 23a),

    t.sub.x+1,y-1 t.sub.x+1,y t.sub.x+1,y+1

is input to a linear operation by a rectangular matrix, L, of the samesize (3×3 in this example) to produce a single output value for thesecond derivative value of the central pixel (t_(x),y →t"_(x),y) at thatpoint.

That convolution can be represented as follows:

     T"!= L!⊙ T!                                  (5)

Thus, the value of each element of the second derivative image asdefined in FIG. 23b can be expressed mathematically as: ##EQU3##

In this operation, however, there is an erosion at the edges of thetransmission pixel image in that the resulting T" image matrix as shownin FIG. 23b has no values in the outer most rows and columns around theedge of that image.

The selection of L for performing the second derivative function cantake many forms. The values for L illustrated here is a Lambertiantechnique that is common in the art, and one that is symmetric in twodimensions since the transform here is being performed in twodimensions. L in this example has been selected to have a spectralresponse in the other domain that is as circularly symmetric aspossible.

Thus, through this operation, the T→T" and R→R" transformations areperformed. For purposes of illustration here, the second derivative ofthe T or R pixelized images is computed by approximating it with a highpass filter, L, or convolution matrix: ##EQU4## where typical valuesare: c=0.1817536, d=0.01539003 and v=h=-0.0648287.

An alternate implementation to the convolution operation on digitizedpixel data is to optically process the image using the well-knownFourier filtering techniques with coherent light to perform thehigh-pass filtering before the sampling process.

Methods of Reference Map Generation

As mentioned above, the T-R, T-T", and R-R" detection spaces areutilized to characterize the behavior of a substrate under inspection bybounding the non-defective regions in each detection space. In fact, thesuccess of the method of the second aspect of the present inventionrests on being able to define the boundaries of the defect-free regionsin the T-R, T-T" and RR" spaces. The definitions of those regions foreach reference map are necessary for satisfactory defect detection;additionally, each reference map may contain defect classification zoneswhich are adjustable as desired according to the response of the defectsto the inspection process.

Experiments have shown that substrate characteristics vary sufficientlyso that the defect-free boundaries have to be determined for eachsubstrate in order to optimize the inspection sensitivity for thatsubstrate. On the contrary, the defect classification regions are moregeneric to the inspection method than the substrate, and errors inclassification have a lower cost value than errors in detection.Therefore, the classification zones will be adjusted less frequently inpractice, and can be adjusted by heuristic and long-term statisticalanalysis of defect characteristics.

The purpose of this section is to explain how nominal non-defectivesubstrate information is obtained and encoded in the detection space(i.e. experimental determination of shapes and tolerance regions ofdefect free zones in T-R, T-T" and R-R" spaces). Analytical methods fordetermining the defect-free region in the T-R reference map aredescribed below with these methods carrying over to the determination ofthe defect-free boundaries for the T-T" and R-R" reference maps.

Generally, reference mapping can be regarded as a training process wherethe nominal behavior of the substrate type is observed by arepresentative sampling of a defect-free area of a selected number ofsubstrates of the same type to account for production tolerances. Itshould be noted that reference curves can be developed using a singlesubstrate, however, the use of several provides a better statisticalaverage and the possibility of overcoming the inclusion of a defect onone of the sample substrates. Thus, each substrate used for set-up ofthe system is sampled in the same area and the T, R, T", and R" signalsmeasured at the sample points, and those signals are then plotted indetection space as a record of the sample population.

Filtering (described below) is then performed on this data record inorder to approximate the true statistical behavior of defect-free pixelsfor the particular type of substrate used to develop the defect-freeareas in each of the reference maps. Thus, this process creates areference map with each point designated as defective or non-defectiveby a binary value. The reference map so developed may then be extendedto other values and further encoded for defect classification purposes.

In particular, an area on the substrate with representativephotolithographic patterns is chosen to serve as a typical referencesample for the substrates under inspection. This sample region can bechosen by an operator of the inspection system or automatically undercontrol of the system computer. With either method of choosing thereference sample region for reference locus characterization, it isnecessary to ensure, as much as possible, that the reference sample isfree of defects. Once the reference samples are chosen, transmitted andreflected light images of the reference samples in the selected regionare acquired.

At this point, a number of methods may be applied to obtain thedefect-free region in each of the reference maps. Three of thesemethods, which may be performed by automatic computation are describedbelow.

For example, a binary scatter plot of all pixels taken of the sample(s)may be generated in the T-R plane with every point in T-R space that isoccupied by at least one sample pixel that is assigned a value of one.All remaining unoccupied points in the T-R plane are assigned zerovalues. Typically, most of the occupied points will be concentratedwithin a cluster in envelope 421 (FIG. 20) but there will also be someunoccupied points within that envelope and possibly some occupied pointsoutside that envelope due to anomalies in the sample.

Next this binary scatter plot is operated on to generate a contiguousarea within envelope 421 where all points have unitary value, surroundedby only zeros in the remainder of the T-R plane. To achieve this,standard binary morphological operations are performed, such asdescribed on pp. 384-389 of a book entitled Fundamentals of DigitalImage Operation, written by Anil K. Jain. (Prentice-Hall, EnglewoodCliffs, N.J., 1989.)

Typically, a dilation operation might be applied first, using asymmetric kernel that is at least large enough to remove all the gapsthat were present within the body of the sample cluster between theoriginally sized pixels. The result is a binary distribution which hasbeen filled and expanded.

Similarly, an erosion operation using a symmetric kernel can be used toproduce a reference envelope of the required size. Thus, inspectionsensitivity is controlled by adjusting the size of the final referenceenvelope, and therefore the nature and size of the final operation.Dilation of the envelope reduces sensitivity, while erosion has theopposite effect. In general, the final envelope should be larger thanthe sample cluster since the finite sample cluster only partiallyrepresents the statistical distribution of defect-free points.

For a more accurate representation of the sample data, a multi-valuedhistogram of the reference sample in T-R space might be preferredinstead of a binary scatter plot. Using this approach an actual count ismaintained for each coordinate within T-R space as the sample substratesare scanned to develop the defect-free region in T-R space. Thishistogram can then be smoothed by application of an integrating filter,and converted to a binary-valued map by thresholding.

The advantage of the histogram approach is that T-R points are weightedby their frequency of occurrence, so that rarely occurring T-R pointswill not be weighted as heavily as frequent values during integration.Also, the adjusting of the final threshold controls eliminatesanomalous, infrequently occurring, values from the final T-R referencemap. Further, the width of the integrating filter also allows somesensitivity control.

Another technique of manipulating the sample histogram to define thedefect-free locus is by multi-valued morphology, as explained in a paperby Haralick et al: "Image Analysis Using Mathematical Morphology", IEEETransactions on Pattern Analysis and Machine Intelligence, Vol PAMI-9,No. 4, July 1987. This processing approach is a multi-valued extensionof the binary morphology already cited, defining dilation and erosionoperations on functions with multi-valued range. This approachrepresents something of a hybrid of the previous two approaches, in thatmulti-valued dilations and erosions would be applied, in place of anintegrating filter, to obtain a smoothed histogram, and a finalthreshold operation would reduce the mapping to a binary value.

Other Embodiments

As discussed above, a laser scanning system may be used tosimultaneously generate transmitted and reflected light signal pairs,the method of inspection and defect classification of the second aspectof the present invention can be utilized with any image scanning processwhich is capable of generating synchronized transmitted and reflectedlight signal pairs.

Furthermore, this method of detection and classification can be utilizedwith any image scanning process which is capable of generatingsynchronized multiple light signals, generated by any number of lightdetectors placed in any direction about the substrate, which may beilluminated by any light source directed at any angle toward thesubstrate. As explained in the discussion of the detection space, thenumber and nature of the observables need not be restricted to T, R, T",and R", so long as there is sufficient correlation within theobservables that a reference map can be generated to performsatisfactory detection and classification.

An alternate method for detecting and classifying defects is with neuralnetwork methods. For example, the detection spaces and reference mapsdeveloped by the processes discussed-above can be implemented as aninput/output mapping with a three-layer backpropagation network (BPN) asdescribed in pp. 89-126 in a book Neural Networks--Algorithms,Applications, and Programming Techniques by J. A. Freeman and D. M.Skapura, Addison-Wesley, Reading, Mass., 1991.

For the neural network approach, requirements on the scanning system arethe same as discussed above with the following modification. A typicalBPN, illustrated in FIG. 25, is composed of three layers of neurons, aninput layer, a hidden processing layer, and an output layer. Each neuronin the input layer receives an observable (e.g. a single pixel of thelocal rectangular neighborhood of pixels discussed above with respect toFIGS. 23a and 23b from both the T and R signals) as an input signal andpasses it to the second, or hidden, layer; each neuron in the hiddenlayer receives all outputs from all neurons in the first layer andgenerates an independent output signal; and each neuron in the thirdlayer receives all outputs from all neurons in the hidden layer andgenerates an independent output signal. Thus, each neuron creates anoutput signal based on a weighted linear activation function of thecombined inputs from all of the nodes in the previous layer. Each ofthose weighted linear activation function having been determined duringthe learning phase through variations in the individual biasing of eachnode of the hidden and output layers. The biasing functions can eitherbe calculated and then applied to the respective biasing unit, or thelearning can be performed in a dynamic environment, even an on-goingprocedure in some applications where not all possible outcomes are knownat the outset. Additional discussion of the learning phase is presentedbelow to further illustrate this process.

It should be noted that, in operation, even though each node in thehidden and output layers receives the output signal from each node ofthe previous layer, not all of those signals are necessarily used in theperformance of the particular function of that particular node. Theinterconnection of all nodes in the previous layer to every node in thenext layer is the result of the standardization used in the productionof the BPN since the effect of various signals can effectively beignored at those nodes where that signal is not of interest. That is,the biasing of each hidden node can be adjusted to generate an outputsignal from that node that is an approximation of the values, forexample, in the T-T" space of the second aspect of the present inventionwhile ignoring the R and R" signals from the input layer nodes.

Thus such a BPN might have four input neurons for the four observablesT, R, T", and R", a hidden layer which measures many differentactivation potentials corresponding to different correlations in thedata, and an output layer which generates a set of membership values,each output neuron node assigned a membership value for a specificdefect class. The final evaluation might be determined by the class withthe maximum membership value. This implementation is actually analternative method for determining the same input-output relationship,referred to as the reference map, which is a generic aspect of thepresent invention. In fact, the input layer corresponds to thecoordinates of the detection space, the output signals correspond to thedefect class assignment for a given input signal, and the hidden layercorresponds to an optimal analytical or logical procedure for assigninga class to each input, as embodied in the reference map.

The backpropagation feature of such a network is used to train theweights in the hidden and output layers so that the desired mapping isachieved and errors are minimized. The training procedure describedpreviously can be easily adapted to this implementation by feeding thesample data through the backpropagation procedure and adjusting theweights to match desired outputs to the inputs. Furthermore,backpropagation allows the BPN to continue training during use whenevera secondary defect verification procedure is required.

Another variation to this approach applies where the network alsoperforms the filtering on the T and R signals, so that the input layerconsists of 18 input neurons, accepting the 9 transmitted values and the9 reflected values contained within a 3 by 3 neighborhood of pixels.

While the second aspect of the present invention has been described inseveral modes of operation and with exemplary routines and apparatus, itis contemplated that persons skilled in the art, upon reading thepreceding descriptions and studying the drawings, will realize variousalternative approaches to the implementation of the second aspect of thepresent invention. It is therefore intended that the following appendedclaims be interpreted as including all such alterations andmodifications that fall within the spirit and scope to the second aspectof the present invention and the appended claims.

What is claimed is:
 1. An inspection system to inspect a substrate forunwanted particles and features, said substrate having a patterned andan unpatterned surface with a pattern of opaque material on saidpatterned surface, said inspection system comprising:an illuminationsystem to provide an illumination beam through a path to a point on saidpatterned surface of said substrate and said pattern thereon with saidpatterned surface of said substrate closest to said illumination system;a transmission detector aligned with said path to detect a transmittedportion of said illumination beam through said substrate from anilluminated point on said patterned surface of said substrate and toprovide a signal representative of said detected transmitted portion ofsaid illumination beam; a reflection detector to detect a portion ofsaid illumination beam reflected from said illuminated point on saidsubstrate and said pattern thereon along said path of said illuminationbeam and to provide a signal representative of said detected reflectedportion of said illumination beam; a comparator to compare said signals,with each other, from said transmission and reflection detectorsdeveloped by illumination of the same point on said patterned surface ofsaid substrate and said pattern thereon to provide a comparison value ofthose signals; a first memory to store expected values of comparisonvalues from said comparator; and a processor coupled to said comparatorand said first memory to determine if said comparison value is anexpected value and to generate a report when an unexpected value isdetermined.
 2. An inspection system as in claim 1 wherein:saidinspection system further includes a translational stage to providetranslational motion between said patterned surface of said substrateand said illumination beam; said comparator further compares signals,with each other, from said transmission and reflection detectors toprovide a comparison value for each point on said patterned surface ofsaid substrate and said pattern thereon; and said processor furtherdetermines if one or more of said comparison values has an expectedvalue and generates a report when at least one unexpected value isdetermined.
 3. An inspection system as in claim 1 wherein:saidinspection system further comprises a second memory to store the signalfrom one of said transmission and reflection detectors; and saidcomparator receives one of said transmission and reflection signals forcomparison from said second memory and the other one of saidtransmission and reflection signals from the corresponding one of saidtransmission and reflection detectors from the same point on the surfaceand said pattern thereon of said substrate when both signals areavailable.
 4. An inspection system as in claim 2 wherein:said inspectionsystem further comprises a second memory to store the signal from one ofsaid transmission and reflection detectors and a designation of thecorresponding illuminated point on said patterned surface of saidsubstrate and said pattern thereon for each stored signal; and saidcomparator receives one of said transmission and reflection signals forcomparison from said second memory and the other one of saidtransmission and reflection signals from the corresponding one of saidtransmission and reflection detectors from the same point on the surfaceand said pattern thereon of said substrate when both signals areavailable.
 5. An inspection system as in claim 1 wherein:said inspectionsystem further comprises a second memory to store a plurality of signalpairs comprising one signal from each of said transmission andreflection detectors resulting from the illumination of the patternedsurface of a plurality of substrates of the same design to generate arange of expected values for each of said signals from each of saidtransmission and reflection detectors for each point for substrates ofthe same design; and said processor is coupled to said second memory todetermine if the transmission and reflection signals for each point onthe substrate being inspected are within said range of expected values.6. An inspection system as in claim 2 wherein:said inspection systemfurther comprises a second memory to store a family of a plurality ofsignal pairs comprising one signal from each of said transmission andreflection detectors resulting form the illumination of the patternedsurface of a plurality of substrates of the same design to generate arange of expected values for each of said signals from said transmissionand reflection detectors each point for substrates of the same design;and said processor is coupled to said second memory to determine if thetransmission and reflection signals for each point on the substratebeing inspected are within said range of expected values.
 7. Aninspection system as in claim 2 wherein:said inspection system furthercomprises:a second memory to systematically store values from one ofsaid transmission and reflection detectors and the correspondinglocation of the corresponding illuminated point on the patterned surfaceof the substrate for each corresponding illuminated point on thepatterned surface of the substrate; and a function generator disposed toreceive stored values from said second memory to generate a specificfunction from the signal values stored in said second memory; and saidcomparator further compares signals from two or more of saidtransmission detector, reflection detector, and said function generator.8. An inspection system as in claim 7 wherein:said inspection systemfurther comprises:a third memory to systematically store values from theother one of said transmission and reflection detectors and thecorresponding location of the corresponding illuminated point on thepatterned surface of the substrate for each corresponding illuminatedpoint on the patterned surface of the substrate; and said functiongenerator is also disposed to receive stored values from said thirdmemory to generate a specific function from the signal values stored insaid third memory.
 9. An inspection system as in claim 7 wherein saidselected specific function is a second derivative.
 10. An inspectionsystem as in claim 8 wherein said first selected specific function is asecond derivative.
 11. An inspection system as in claim 8 wherein saidsecond selected specific function is a second derivative.
 12. Aninspection system as in claim 1 wherein:said first memory furtherincludes stored therein potential unwanted particle and feature typesand a range of comparison values for each unwanted particle and featuretype; and said processor, when an unexpected comparison value isobtained, further obtains unwanted particle and feature type informationcorresponding to said unexpected comparison value from said first memoryand includes said unwanted particle and feature type information in saidreport.
 13. An inspection system as in claim 2 wherein:said first memoryfurther includes stored therein potential unwanted particle and featuretypes and a range of comparison values for each of said unwantedparticle and feature type; and said processor, when an unexpectedcomparison value is obtained, further obtains unwanted particle andfeature type information corresponding to said unexpected comparisonvalues from said first memory and includes said unwanted particle andfeature type information in said report.
 14. An inspection system as inclaim 13 wherein:said translation stage further generates a positionsignal that corresponds to the location of said illumination point onthe patterned surface of said substrate; said comparator is furthercoupled to said translational stage to receive said positional signalsthat are provided together with said comparison values; and saidprocessor, when an unexpected comparison value is obtained, furtherdecodes said positional signals and provides patterned surface of saidsubstrate location information for each unwanted particle and feature insaid report.
 15. An inspection system as in claim 13 wherein:saidtranslation stage further generates a position signal that correspondsto the location of said illumination point on the patterned surface ofsaid substrate; and said processor is further coupled to saidtranslational stage to receive said positional signals and, when anunexpected comparison value is obtained, further decodes said positionalsignals and provides patterned surface of said substrate locationinformation for each unwanted particle and feature in said report. 16.An inspection system as in claim 1 wherein said first memory includes atolerance value for said stored expected values.
 17. An inspectionsystem as in claim 1 wherein each of said transmission detector andreflection detector are image scanners.
 18. An inspection system as inclaim 1 wherein said processor includes a neural network to process thesignals from each of said transmission and reflection detectors.
 19. Amethod for inspecting a substrate for unwanted particles and features,said substrate having a patterned and an unpatterned surface with apattern of a opaque material on said patterned surface, said methodincluding the steps of:a. directing an illumination beam through a pathto a point on the patterned surface of said substrate and said patternthereon with said patterned surface closest to a source of saidillumination beam; b. detecting, in alignment with said illuminationbeam of step a., a transmitted portion of said illumination beam throughsaid substrate; c. generating a signal representative of said detectedtransmitted portion of said illumination beam of step b.; d. detecting,along said path of step a., a reflected portion of said illuminationbeam from said patterned surface of said substrate and said patternthereon; e. generating a signal representative of said detectedreflected portion of said illumination beam of step d.; f. generating acomparison value of said signals, with respect to each other, from stepsc. and e.; g. storing expected comparison values; and h. generating areport when the comparison value of step f. does not correspond to anexpected comparison value stored in step g.
 20. A method as in claim 19further including the steps of:i. translating said substrate to a nextposition; and j. repeating steps a. through i. for each point ofinterest on said substrate.
 21. A method as in claim 19 wherein:saidmethod further includes the following step between steps e. and f.:k.storing the signal from one of steps c. and e.; and said step f.generates said comparison value from the signal stored in step k. andthe unstored one of the signals from steps c. and e. from the same pointon the surface of said substrate when both signals are available.
 22. Amethod as in claim 20 wherein:said method further includes the followingstep between steps e. and f.:l. storing the signal from one of steps c.and e. for each point illuminated on the patterned surface of saidsubstrate; and said step f. generates said comparison value for eachpoint on said substrate from the signal stored in step k. for that pointand the unstored one of the signals from steps c. and e. for the samepoint on the substrate when both signals are available.
 23. A method asin claim 19 wherein:step g. further includes the step of:m. storing atleast one potential unwanted particle and feature type and a range ofunexpected comparison values that corresponds to that unwanted particleand feature type; and step h. further includes the step of:n. includingunwanted particle and feature type information from step m. in thegenerated report.
 24. A method as in claim 20 wherein:step g. furtherincludes the step of:o. storing at least one potential unwanted particleand feature type and a range of unexpected comparison values thatcorresponds to that unwanted particle and feature type; and step h.further includes the step of:p. including unwanted particle and featuretype information from step o. in the generated report.
 25. A method asin claim 20 wherein:step i. includes the step of:q. generating aposition signal that corresponds to the point on said substrate beingilluminated in step a.; step f. includes the step of:r. identifying theposition signal from step q. that corresponds to each generatedcomparison value; and step h. includes the step of:s. including in saidreport the corresponding point on said substrate from step r. where anunwanted particle and feature was detected.
 26. A method as in claim 20wherein:step i. includes the step of:t. generating a position signalthat corresponds to the point on said substrate being illuminated instep a.; and step h. includes the step of:u. including in said reportthe corresponding point on said substrate from step t. where an unwantedparticle and feature was detected.
 27. A method as in claim 19 whereinstep g. also includes the storing of a tolerance for the stored expectedcomparison values.
 28. A method for inspecting a substrate for unwantedparticles and features, said substrate having a patterned and anunpatterned surface with a pattern of opaque material on said patternedsurface, said method including the steps of:a. selecting a substrate ofthe type to be inspected; b. directing an illumination beam through apath to a point on the patterned surface of said substrate and saidpattern thereon with said patterned surface closest to a source of saidillumination beam; c. detecting, in alignment with said illuminationbeam of step b., a transmitted portion of said illumination beam throughsaid substrate; d. generating a signal representative of said detectedtransmitted portion of said illumination beam of step c.; e. detecting,along said path of step b., a reflected portion of said illuminationbeam from said patterned surface of said substrate; f. generating asignal representative of said detected reflected portion of saidillumination beam of step e.; g. generating an expected comparison valueof said signals from steps d. and f. with respect to each other; h.storing said expected comparison value of step g.; i. repeating steps a.through h. for a selected number of different substrates of the type tobe inspected; j. selecting a particular substrate to be inspected; k.directing an illumination beam through a path substantially normal to apoint on the patterned surface of said substrate of step j.; l.detecting, in alignment with said illumination beam of step k., atransmitted portion of said illumination beam through said substrate ofstep j.; m. generating a signal representative of said detectedtransmitted portion of said illumination beam of step l.; n. detecting,along said path of step k., a reflected portion of said illuminationbeam from said patterned surface of said substrate of step j. and saidpattern thereon; o. generating a signal representative of said detectedreflected portion of said illumination beam of step n.; p. generating acomparison value of said signals, with respect to each other, from stepsm. and o.; and q. generating a report when the comparison value of stepp. does not correspond to an expected comparison value stored in step h.29. A method as in claim 28 wherein step g. also generates a tolerancevalue for said comparison value.
 30. A method for inspecting a substratefor unwanted particles and features, said substrate having a patternedand an unpatterned surface with a pattern of opaque material on saidpatterned surface, said method including the steps of:a. selecting asubstrate of the type to be inspected; b. directing an illumination beamthrough a path to a point on the patterned surface of said substrate andsaid pattern thereon with said patterned surface closest to a source ofsaid illumination beam; c. detecting, in alignment with saidillumination beam of step b., a transmitted portion of said illuminationbeam through said substrate; d. generating a signal representative ofsaid detected transmitted portion of said illumination beam of step c.;e. detecting, along said path of step b., a reflected portion of saidillumination beam from said patterned surface of said substrate and saidpattern thereon; f. generating a signal representative of said detectedreflected portion of said illumination beam of step e.; g. generating anexpected comparison value of said signals from steps d. and f. withrespect to each other; h. storing said expected comparison value of stepg.; i. translating said substrate to a next position; and j. repeatingsteps a. through i. for each point of interest on said substrate of stepa.; k. repeating steps a. through j. for a selected number of differentsubstrates of the type to be inspected; l. selecting a particularsubstrate to be inspected; m. directing an illumination beam through apath to a point on the patterned surface of said substrate of step l.and said pattern thereon with said patterned surface closest to a sourceof said illumination beam; n. detecting, in alignment with saidillumination beam of step m., a transmitted portion of said illuminationbeam through said substrate of step l.; o. generating a signalrepresentative of said detected transmitted portion of said illuminationbeam of step n.; p. detecting, along said path of step m., a reflectedportion of said illumination beam from said patterned surface of saidsubstrate of step
 1. and said pattern thereon; q. generating a signalrepresentative of said detected reflected portion of said illuminationbeam of step p.; r. generating a comparison value of said signals, withrespect to each other, from steps o. and q.; s. storing said comparisonvalue of step r.; t. translating said substrate to a next position; u.repeating steps m. through s. for each point of interest on saidsubstrate of step l.; v. generating a report when any comparison valuefor a particular point on said substrate of step l. stored by of step s.does not correspond to an expected comparison value stored in step h.for the same point on substrates of the same type.
 31. A method as inclaim 30 wherein step g. also generate a tolerance value for saidexpected comparison value.
 32. A method for inspecting a substrate forunwanted particles and features, said substrate having a patterned andan unpatterned surface with a pattern of opaque material on saidpatterned surface, said method including the steps of:a. directing anillumination beam through a path to a point on the patterned surface ofsaid substrate and said pattern thereon with said patterned surfaceclosest to a source of said illumination beam; b. detecting, inalignment with said illumination beam of step a., a transmitted portionof said illumination beam through said substrate; c. generating a signalrepresentative of said detected transmitted portion of said illuminationbeam of step b.; d. detecting, along said path of step a., a reflectedportion of said illumination beam from said patterned surface of saidsubstrate and said pattern thereon; e. generating a signalrepresentative of said detected reflected portion of said illuminationbeam of step d.; f. storing the generated signals of steps c. and e.together with the location of the point illuminated in step a.; g.translating said substrate to a next position; and h. repeating steps a.through f. for each point of interest on said substrate and said patternthereon; i. generating a signal corresponding to a first selectedfunction value of the signal values for one of the stored transmissionand reflection signals of step f. for each point of interest on thesubstrate being inspected; j. storing the signal values generated instep i. together with the corresponding point on the surface of saidsubstrate; k. generating expected comparison values for each combinationof the three values stored in steps f. and j. for each point of intereston a substrate of the type being inspected; l. generating a comparisonvalues of two or more of said signal values from steps f. and j., withrespect to each other, for each point of interest on the substrate beinginspected; m. generating a report when the comparison value of step l.for any point of interest on the substrate being inspected does notcorrespond to an expected comparison values stored in step
 1. for thatpoint on the surface of substrates of the same type.
 33. A method as inclaim 32 wherein step k. also generates a tolerance value for saidexpected comparison values.
 34. A method as in claim 32 wherein step i.further includes:n. generating a signal corresponding to a secondselected function value of the signal values for the other one of thestored transmission and reflection signals of step f. for each point ofinterest on the substrate being inspected.
 35. A method as in claim 32wherein said first selected function of step i. is a second derivative.36. A method as in claim 34 wherein said first selected function of stepi. is a second derivative.
 37. A method as in claim 34 wherein saidsecond selected function of step n. is a second derivative.
 38. Aninspection system to simultaneously inspect a substrate for defects, andunwanted particles and features, said substrate having a patterned andan unpatterned surface with a pattern of opaque material on saidpatterned surface, said inspection system comprising:an illuminationsystem to provide an illumination beam through a path to a point on saidpatterned surface of said substrate and said pattern thereon with saidpatterned surface of said substrate closest to said illumination system;a transmission detector aligned with said path to detect a transmittedportion of said illumination beam through said substrate from anilluminated point on said patterned surface of said substrate and toprovide a signal representative of said detected transmitted portion ofsaid illumination beam; a reflection detector adjacent said patternedsurface of said substrate to detect a portion of said illumination beamreflected from said illuminated point on said substrate along said pathof said illumination beam and to provide a signal representative of saiddetected reflected portion of said illumination beam; a first comparatorcoupled to each of said transmission and reflection detectors to comparesaid signals from each of said detectors, with each other, developed byillumination of the same point on said patterned surface of saidsubstrate to provide a first comparison value of those signals; a memoryhaving expected values of said first comparison value from said firstcomparator stored therein; a database containing the value of a pair ofexpected signals from said transmission and reflection detectors for apoint being inspected for the particular type of substrate beinginspected; a second comparator coupled to each of said transmission andreflection detectors and said database to compare a value of each ofsaid signals from said transmission and reflection detectors with thevalues of the expected pair of transmission and reflection detectorsignals from said database to identify the presence of a defect at thepoint of inspection on said substrate; and a processor coupled to saidfirst and second comparators and said first memory to determine whensaid first comparison value is an unexpected value and to identify thetype of unwanted particle or feature when an unexpected value isdetermined.
 39. An inspection system as in claim 38 wherein:saidinspection system further includes a translational stage having saidsubstrate mounted thereon to provide translational motion between saidpatterned surface of said substrate and said illumination beam; saidfirst comparator further compares signals, with each other, from saidtransmission and reflection detectors at each point on the patternedsurface of said substrate to provide a first comparison value for eachpoint on said patterned surface of said substrate; said database storesa pair of expected values of signals from said transmission andreflection detectors together with positional data for each point beinginspected on the patterned surface of said substrate, said stored valuesand corresponding positional data is for the particular type ofsubstrate being inspected; said second comparator further compares saidsignals from said transmission and reflection detectors from each pointon the patterned surface of said substrate with the values of theexpected pair of transmission and reflection detector signals from saidsecond memory for each point on the patterned surface of said substrateto identify the presence of defects at all points on the patternedsurface on said substrate; and said processor further determines if oneor more of said first comparison values has an unexpected value andgenerates a report when at least one unexpected value is determinedidentifying the type of each unwanted particle or feature correspondingto each of said first comparison values.
 40. A method for simultaneouslyinspecting a substrate for defects, and unwanted particles and features,said substrate having a patterned and unpatterned surface with a patternof opaque material on said patterned surface, said method including thesteps of:a. directing an illumination beam through a path to a point onthe patterned surface of said substrate with said patterned surfaceclosest to a source of said illumination beam; b. detecting, inalignment with said illumination beam of step a., a transmitted portionof said illumination beam through said substrate; c. generating a signalvalue representative of said detected transmitted portion of saidillumination beam of step b.; d. detecting, along said path of step a.,a reflected portion of said illumination beam from said patternedsurface of said substrate and said pattern thereon; e. generating asignal value representative of said detected reflected portion of saidillumination beam of step d.; f. generating a first comparison value ofsaid signal values, with respect to each other, from steps c. and e.; g.storing expected first comparison values; h. storing a pair of expectedvalues of said signal values representative of said detectedtransmission and reflected portions of said illumination for theparticular type of substrate being inspected; i. individually comparingeach of said signal values of steps c. and e. to the expected value ofeach of said signal values of step h.; j. generating a report when thecomparison value of step f. does not correspond to an expectedcomparison value stored in step g. and also if either of the signalsdoes not agree with an expected value in step i.
 41. A method as inclaim 40 wherein:said method further includes the step of: k. providingmotion relative to the patterned surface of said substrate and saiddirected illumination beam of step a.; said step h. further includesstoring a pair of expected values of said signal values representativeof said detected transmission and reflected portions of saidillumination and corresponding positional data for each pointilluminated on the patterned surface the particular type of substratebeing inspected; and said method further includes the said step of: l.repeating steps a. through f. and i. through j. for each pointilluminated on the patterned surface of said substrate.